Idea About Fraud Detection Using Different Algorithms Computer Science Essay
The first algorithm that the writer has used is mining the symbolic information. This algorithm is based on the thought that misused dealing are seen as a sort of regulation. The advantage of this is, Uniting a figure of abuse regulations which leads us to shorten the regulations and diminish the dependence. The other regulations is called excavation parallel informations. This regulations is based on covering with parallel informations. Here the job of fraud analysis is based on dividing two sorts of categories of events. This algorithm leads us to high fraud sensing and high assurance. In last the writer used another technique by uniting regulation based association algorithm and web information in determination web. When this system is used in parallel so this shows mistake in big sum along with low assurance. Beside that this system is used in consecutive as good. Now the advantage of this system is that the parallel informations first base on ballss through parallel cheque and so moves frontward for consecutive cheque, which leads us to high informations rightness and high assurance every bit good.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
R.Bruce, T.langsdorf, M.hepp, frankfur A. M
Neural informations excavation for recognition card sensing
A-
IEEE
Mining the symbolic informations, mining the parallel informations, uniting symbolic and parallel informations
3
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A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
Statistic based recognition card fraud sensing
a?s
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A Neural web algorithm
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a?s
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Pruned web
Advantage
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
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High rightness and high assurance
Traditional V advanced
Decisions
A-
A-
Tables and graphs
1 ) R.Bruce, T.langsdorf, M.hepp, frankfur A. M. Neural informations excavation for recognition card sensing
[ 2 ] This paper is based on effectual informations excavation utilizing nervous web. The paper shows an attack to happen out symbolic categorization set of Torahs by agencies of nervous web. Whereas nervous web is foremost qualified to achieve the obligatory preciseness gait. Furthermore the unnecessary nexus of web are detached by mean of web sniping procedure. The activation rules of the unobserved component in the system are evaluated. Which leads us to the categorization regulations of peculiar analysis. Research is conducted on this planned attack utilizing a distinguishable set of informations mining trouble. And the result demonstrate that high quality of regulations can be exposed from the known informations sets.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Hongjun Lu, Rudysetiono huan liu
Effective informations excavation utilizing nervous web
1996
IEEE
Finding symbolic categorization utilizing nervous web
3
38
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Smaller in size
To bring forth regulations similar to determination tree
A-
a?s
Categorization utilizing nervous web
A-
a?s
A-
Pruned web
Advantage
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
To cut down developing clip of nervous web
Extracting regulations from trained nervous web
Rules
A-
Advanced
A-
2 ) Hongjun Lu, Rudysetiono huan liu. 1996 Effective informations excavation utilizing nervous web
[ 3 ] This paper is based on adoptive nervous web theoretical account for fiscal survey. Data excavation plays cardinal function in happening inhumed prognostic information from bulky catalog. Artificial nervous web which is normally used by informations excavation technique, is an algorithm used for this intent. This proposed attack has been tested with map estimate and stock market minute survey. And from these experimental information we can weave up that the future attack is much better to bing standard ANN for the usage of informations excavation. And we can see that our new ANN with NAF can hike trained velocity, shrink web size and simulation mistake. And besides supply us more promising results.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Dr Shuxiang xu, Prof Ming Zang
An adoptive nervous web theoretical account for fiscal analysis
2005
Journal
Artificial nervous web
2
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
To research ANN with NAF for fiscal analysis
a?s
a?s
A-
A-
a?s
A-
Pruned web
Advantage
Related model/algorithm
Application type
Based on
Type of informations
Algorithm type
Data presentation
A-
Reduce web size and simulation mistake
Neuron adoptive activation map
NAF and ANN
Rules
A-
Advanced
Graph
3 ) Dr Shuxiang xu, Prof Ming Zang. 2005 An adoptive nervous web theoretical account for fiscal analysis
[ 4 ] this paper describes the execution of unreal nervous web in field of solid ducted projectile trial. This paper describes the brief execution of unreal nervous web theoretical account. Further more it tells that ANN is combined with RBF ( redial footing map ) to retrieve the unnatural informations. The ANN theoretical account is based on 3 superimposed architecture. Which takes informations on input node so transform it to middle bed called concealed node so it moves toward the end product node. When information moves toward the concealed node so it applies informations excavation techniques on big informations and happen the correlativity between different informations. This algorithm detects and retrieve the guerrilla parametric quantities quickly and expeditiously.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Qiang liu, futting bao, bingge xia, xi’an P.R
Data analysis and SDR trial based on ANN theoretical account
2012
A-
Radial footing map
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
Still under procedure of development
A-
a?s
Artificial nervous web
SDR trial
A-
A-
Pruned web
Advantage
Related model/algorithm
Application type
Based on
Type of informations
Algorithm type
Data presentation
A-
Detect and retrieve the unnatural parametric quantity efficaciously
k-mean bunch algorithm
ANN layered based
Rules
Test information
A-
A-
4 ) Qiang liu, futting bao, bingge xia, xi’an P.R 2012 Data analysis and SDR trial based on ANN theoretical account
[ 5 ] This paper tells us about the execution of informations mining attack in urban H2O system. In information excavation attack further they implement nervous web attack. Further more in item they introduced self-organizing maps attack in nervous web. The occupation of which is to roll up DNA based molecular techniques and to analyse environmental samples. in microbiology to group different samples. Comparison of many T-RFLP ( terminal limitation fragment length polymorphism ) profiles to discovercollective and singlecomponents of microbiology community. T-Align package is used for grouping these things. The chief benefit of this attack is the capableness to show the information in a ocular manner that offers effortless visual image and apprehension of multi-dimensional and complex informations sets.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Stephen R. mounce, henriette S.jensen, Catherine A.biggs, joby B. boxall
T-RFLP profiles from urban H2O system trying utilizing SOM maps
2012
A-
Artificial nervous web utilizing SOM map
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
To larn the growing of this attack for thought to distributed construction
a?s
A-
T-align package
Urban H2O system
A-
A-
Pruned web
Advantage
Related model/algorithm
Application type
Based on
Type of informations
Algorithm type
Data presentation
A-
The accomplishment to demo the informations in ocular manner, account of complex informations sets
Traditional statistical methods
ANN layered based
Rules
Man-made informations
Supervised/unsupervised
Unobserved to ocular
5 ) Stephen R. mounce, henriette S.jensen, Catherine A.biggs, joby B. boxall 2012 T-RFLP profiles from urban H2O system trying utilizing SOM maps
[ 6 ] In this paper the writer describes the unsupervised ocular information excavation utilizing SOM and a information driven colour function. The writer uses two different algorithm for happening the solution of this job. The 1st method that the writer used is SOM ( self-organizing map ) . This algorithm output two dimensional and irregular representation of the input records. Blinchard ‘s attack utilizes this information as input and associates this input informations to a pel in a figure. The algorithm is a well-organized manner to visualise the typical and big informations. Finally he do usage of these reference algorithm collectively.Which leads us to obtain a wholly unverified ocular informations excavation instrument. Where the colour function is data driven. The proving result of this attack offers visual image that permit the taking out of bunch. The unverified mechanization of the colouring allows us to nuance the fond regard of a category.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Cyril De Runz, Eric desjardin, Michel Herbin, crestic
Unsupervised informations excavation utilizing SOM & A ; informations driven colour function
2012
Journal
Kohonen map and blanchard attack
2
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
choosing ill-defined agronomical size and cooperate within GIS.
A-
a?s
k-mean and MATlab
A-
A-
A-
Pruned web
Advantage
Related model/algorithm
Application type
Based on
Type of informations
Algorithm type
Data presentation
A-
A-
k-means, MATlab tool chest
Combination of SOM and colour function
Decision/rule based
Real informations unknown
Unsupervised
Ocular
6 ) Cyril De Runz, Eric desjardin, Michel Herbin, crestic 2012 Unsupervised informations excavation utilizing SOM & A ; informations driven colour function
[ 7 ] The subject of the writer is to do different bunchs utilizing informations excavation technique. He make usage of self-organizing map ( SOM ) to carry through his end. The purpose of SOM is to map multi-dimensional input into two dimensional signifier. This tactic is used for constellating and categorization intent. The regulations are extracted from trained SOM ‘s. which can so calculate the prepositional IFaˆ¦ THEN type system. These effortless set of Torahs can be easy broken by expert or determination support system and are merely explainable to an expert. The jurisprudence signify the trained SOM in instances where bunch has volitionally taken topographic point. The of import characteristic of this jutting strategy is the underlying exactitude of constellating process achieved by SOM. In instance where the SOM non win to readily constellate the facts, the resulting system will retroflex this original inexactitude.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
James Malone, Kenneth McGarry, Safan Wermter, Chris Buwerman
Data excavation utilizing rule extraction from kohhnen SOM
2005
Journal
Self-organizing maps
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Smaller in size
A-
a?s
a?s
A-
A-
A-
A-
Pruned web
Advantage
Related model/algorithm
Application type
Based on
Type of informations
Algorithm type
Data presentation
A-
critical truth of constellating path execute by SOM
Extracting regulations
Combination of SOM and colour function
Rule based
Real informations
Unsupervised
Clustering of different informations
7 ) James Malone, Kenneth McGarry, Safan Wermter, Chris Buwerman 2005 Data excavation utilizing rule extraction from kohhnen SOM
[ 8 ] In this paper the writer describes a fresh attack for Expert system application. He make usage of an algorithm called MTS ( Mahalanobis-Taguchi system ) -ANN ( unreal nervous web ) in expert system. He implements this algorithm in dynamic environment. The experimental results of this algorithm turn out that this algorithm is vastlyvalid in pattern acknowledgment and is computationally efficient in add-on to the ANN algorithm is a straightforward and resourcefulsystem for piecing a dynamic construction. From this it can be accomplished that MTS-ANN algorithm can be efficaciously utile to dynamic environment for data-mining problems.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Ching-lien huang, tsung-shin hsu, chih-ming liu
The MTS-ANN algorithm for informations excavation in dynamic environments
2009
Journal
MTS-ANN
1
Large informations sets
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Smaller in size
MTS-ANN algorithm can be used in dynamic environment absolutely
a?s
a?s
Statistical informations, charts
Dynamic environment
A-
A-
Pruned web
Advantage
Related model/algorithm
Application type
Based on
Type of informations
Algorithm type
Data presentation
A-
Pattern acknowledgment, theoretical account building and high assurance
Linear correlativity discovering ( LCD )
Combination of SOM and colour function
Rule/statistical based
Real informations
A-
Charts and tabular arraies
8 ) Ching-lien huang, tsung-shin hsu, chih-ming liu 2009 The MTS-ANN algorithm for informations excavation in dynamic environments
[ 9 ] The given paper shows machine acquisition and information excavation application for the anticipation of impetuss in engineering skilled turnover rates of the employees. Then he used an algorithm which is the combination of two different algorithm i.e SOM ( self forming map ) and BPN ( back extension nervous web ) . This algorithm combines the advantages of SOM and BPN which applied on the expose belongingss associated to turnover tendencies cluster. With the aid of this algorithm we come to cognize that this algorithm is the best algorithm for happening out the turnover of employees and besides demoing the factors which involve in increasing the rate of the employees turnover.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Chin-yaun fan, pei-shu Fan, te-ye chan, shu-hao Shang
Using intercrossed informations excavation and machine larning constellating analysis to foretell the turnover rate for engineering professional
2012
Journal
constellating analysis ( SOM ) plus Back extension neural web
3
421 valid inquirers
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
A-
a?s
Using informations excavation tools
Using informations excavation methodological analysis
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
SOM and nervous web constellating method
Rules
Real clip informations
Inquirers
Charts and graphs
9 ) Chin-yaun fan, pei-shu Fan, te-ye chan, shu-hao Shang 2012 Using intercrossed informations excavation and machine larning constellating analysis to foretell the turnover rate for engineering professional
[ 10 ] In this proposed paper the writer introduces a new nervous attack known as ensemble recursive regulation extraction. This attack is fundamentally excavation of regulations from the ensemble nervous web. In this attack we come to cognize that the proposed attack produces higher acknowledgment truth as compared to the single nervous web. Where the mined regulations are more comprehendible. The proposed attack gives more regulations than the old attacks. For nervous informations analysis this proposed attack promises a new attack. So it is clear that in future this attack will be used to intensify the chances to utilize informations excavation for the intent of high informations acknowledgment.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Atsushi Hara, Yoichi Hayashi
New nervous informations analysis attack utilizing ensemble nervous web regulation extraction
2012
ICAN
Ensemble Recursive Rules Extraction ( E-Re-Rx )
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Large sum on memory
Using informations excavation with high acknowledgment truth
A-
a?s
Using nervous web regulations
Geting of regulations from ensemble nervous web
a?s
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
A-
Rules
Learning informations sets
A-
A-
10 ) Atsushi Hara, Yoichi Hayashi 2012 New nervous informations analysis attack utilizing ensemble nervous web regulation extraction
[ 11 ] Covering with the anticipations of the victor of the college football squad is a challenging and interesting undertaking. The old surveies shows us that all the old anticipation were failed because they were covering with the ranking and force of the squad. Here the writer has predicted a fresh attack the writer used three techniques ( unreal nervous web, support vector machine and determination trees ) the intent of utilizing these technique is to make arrested development and categorization sort of theoretical accounts so that to reexamine different methodological analysiss anticipation ability.This method proved that this attack is better manner to show the future anticipations and can supply a batch of accurate consequences than the old anticipations.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Dursun Delen, Douglas Cogdell, Nihat Kasap
A comparative analysis of informations mining methods in foretelling NCAA bowl results
2012
Journal
CRISP-DM
3
244 Bowl Games
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
Enrichment of variable set, placing and including more input variable
A-
a?s
Decision tree
Artificial nervous web
Support vector machine
Predicting the results of the college football games
a?s
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
A-
Rules and anticipations
Real informations
A-
Chart and graphs
11 ) Dursun Delen, Douglas Cogdell, Nihat Kasap 2012 A comparative analysis of informations mining methods in foretelling NCAA bowl results
[ 12 ] The writer predict a new intelligent attack which will calculate the frequent growing of package which is base on theof the functional webs calculating model. There are tonss of other methods which forecast the anticipation of the package development. But all these failed because these have figure of drawbacks like how to cover with the uncertainnesss. The planned attack has high inclination to cover with the adult environment of recent package advancement. The consequence shows that this method is far better than so other attacks, its public presentation is certain and give us a smallest MAPE value.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Emad A. El-Sebakhy
Functional web as a fresh information excavation paradigm in calculating package development attempt
2011
Journal
Functional web intelligent system
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
To utilize different independent other than multinomial to utilize for informations bases
A-
A-
Nervous web and functional web
Forecasting to the package development attempts
A-
Artificial nervous web
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
LOC, COCOMO, Function Point ( FP )
anticipations
A-
Functional web calculating frame work
Graph
12 ) Emad A. El-Sebakhy 2011 Functional web as a fresh information excavation paradigm in calculating package development attempt
[ 13 ] The motivation of this paper is to cover with non-financial and fiscal ratios of the fiscal statements. For the association of public presentation of the fiscal hurt anticipation, he make usage of the bunch and BPN mold. So that to acquire an early dismay. From the consequences of the method he comes to cognize four major critical properties. The 1st is that every bit more as we are utilizing the factor analysis our consequence for bunch and BPN will be less accurate. 2nd is that that every bit shortly as we get close to the existent fiscal hurt, we will catch more precise result. 3rd is BPN has lower mean rate of type two mistakes as comparison to the constellating model.In 4th the last phase the BPN provide a better and efficient anticipation as that of the DM bunch attack.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Wei-Sen, Yin-kuan Du
Using nervous webs and informations excavation techniques for the fiscal hurt anticipation theoretical account
2009
Journal
Artificial nervous web and information excavation techniques
1
Large sum of records
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Large sum of memory
Using bing techniques to cover with more fiscal datasets
a?s
a?s
ANN and informations excavation
Financial hurt environment
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
a?s
BPN, constellating and categorization
Rules and statistical computation
Supervised/unsupervised
Supervised/unsupervised
Charts and graphs
13 ) Wei-Sen, Yin-kuan Du 2009 Using nervous webs and informations excavation techniques for the fiscal hurt anticipation theoretical account
[ 14 ] The subject of the paper is to roll up information about chest malignant neoplastic disease disease. Which is known as a serious malignant neoplastic disease disease through out the Earth. The end of this writer is to split adult female in two classs i.e the adult female who has wide verifications of holding chest malignant neoplastic disease are grouped into malignant and holding no chest disease are grouped into benign.So the writer tried to suggest such a intercrossed chest cancerdiagnose system by fall ining together unreal nervous web and MRAS. This method is so combine with the BPN. Now in this instance this theoretical account has high categorization truth. Form the consequence of the loanblend and the combination of intercrossed and BPN it is clear that Hybrid and BPN provide tonss of truth but the chief advantage of intercrossed system is that it can salvage tonss of execution clip which consequences in doing shorten the clip for on clip determinations.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Shienu-Ming Chou, Tian -Shyug Lee, Yuehjen E.Shao, I-Fei Chen
Mining the chest malignant neoplastic disease form utilizing unreal nervous web and multivariate adaptative arrested development splines
2004
Data excavation technique with multivariate adoptive arrested development splines ( MARS )
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Large sum
Roll uping more of import variable that addition categorization truth
a?s
a?s
Artificial intelligence and informations excavation techniques
Woman wellness attention
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
BPN
Rules and determinations
A-
A-
Charts and graphs
14 ) Shienu-Ming Chou, Tian -Shyug Lee, Yuehjen E.Shao, I-Fei Chen 2004 Mining the chest malignant neoplastic disease form utilizing unreal nervous web and multivariate adaptative arrested development splines
[ 15 ] In this research the writer is funny in the field of transit and wants to use different informations excavation techniques to happen out unsimilarities, similarities. He is cautious to cognize similarities and unsimilarities between two different school of ideas. He moreover made experiments on different technique utilizing complex construction. And happen out that along with the advantage of the complex mold tools it has restriction every bit good. Which is a large hurdle in the manner of happening similarities and unsimilarities. From this he merely concluded that alternatively of utilizing complex mold technique the end of analysing is much of import. Because there are ever premise in all mold attacks. So with the aid of simpler theoretical account give us a good consequence merely like complex one.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
M.G Karlatis, E.I Vlahogianni
Statistical method vs nervous webs in transit research, differences, similarities and some penetrations
2011
Journal
Statistical and computational ideas.
2
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
A-
a?s
Statistical anticipations and unreal intelligence
Transportation research
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
A-
Predictions and old informations
Supervised/unsupervised
A-
charts
15 ) M.G Karlatis, E.I Vlahogianni 2011 Statistical method V nervous webs in transit research, differences, similarities and some penetrations
[ 16 ] In this article the writer focuses on one of major issue in nervous web. Neural web have been used for arrested development and categorization method in past. And the reading of their internal representation were really hard. Now a twenty-four hours, it is clear that for the extraction of the apprehensible representation from trained nervous web algorithm can be derived. The intent of which is to utilize for informations excavation applications. The work mentioned in this paper delivers a generalised process, which can be used for the jobs in bioinformatics. The consequences are truly impressive but the job is that of bring forthing a big sum of informations. Combination of algorithm with the nervous web for the intent of pull outing of information from the trained nervous web is the best solution, which produces high accurate informations along with that produces cognition find. The use of these methods leads to acceptance and high assurance.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Antoney Browne, Brain D. Hudson, David C. Whitley, Martyn G. Ford, Philip Picton
Biological information excavation utilizing nervous webs execution and application of a flexible determination tree extraction algorithm to genomic job spheres
2003
article
Statistical and computational ideas.
2
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
A-
a?s
Statistical anticipations and unreal intelligence
Transportation research
a?s
Matlab/Netlab
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
Trepan Algorithm
Decision tree
A-
Traditional vs new techniques
tabular arraies
16 ) Antoney Browne, Brain D. Hudson, David C. Whitley, Martyn G. Ford, Philip Picton 2003 Biological information excavation utilizing nervous webs execution and application of a flexible determination tree extraction algorithm to genomic job spheres
[ 17 ] In this article the writer is covering with the anticipation of gully induction. In past predicting gully induction was prepared with the aid of GIF strategy with cognition base expert system, physical based system or statistical processs. But while using these processs cogency and dependability are large issues. For the designation and hazard of gully initiation a process known as Data excavation which is based on determination trees is applied. In this article the comparing of DM technique is shown with many other processs like expert system and topographic threshold method ( TT ) . The consequences show that DM technique provides more accurate informations than that of the other methods. So it is obvious that for the survey of the erroneous process and gully initiation a valuable technique is DM technique.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Tal Svoray, Evgenia Michailov, Avraham Cohen, Lior Rokah and Arnon Sturm
Predicting gully induction: Comparing informations excavation techniques, analytical hierarchy procedures and the topographic
2012
Article
Data excavation process based on determination trees
1
10
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Large sum
a?s
a?s
A-
Transportation research
a?s
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
Decision tree algorithm, ANN, TT, AHP
Rules and statistical analysis
Test information
Traditional V DM techniques
Graph, charts and tabular arraies
17 ) Tal Svoray, Evgenia Michailov, Avraham Cohen, Lior Rokah and Arnon Sturm 2012 Predicting gully induction: Comparing informations excavation techniques, analytical hierarchy procedures and the topographic
[ 18 ] The purpose of this paper is to analyze the scalability of PNN ( probabilistic nervous web ) through localisation, a concatenation gradient tuning and correspondence. As PNN theoretical account is working in analogues so three good cognize attacks are studied here. Two fast estimate solutions are proposed by writer in this paper. The chief purpose of this paper is to speed up the PNN theoretical account with the aid of 24 processors. And the consequence obtained reveals that PNN developing along with subtractive bunch attacks and cross proof can amazingly intensify 24 times. The 2nd issue is how to extinguish the sigma parametric quantity without major loss in PNN public presentation. Clustering within categories the most representative points are selected. Which consequences a localised PNN holding bantam form Neuran Size and first-class public presentation, which is 10 times faster as comparison to that of original version. For the most first-class PNN architecture, tuning can execute to utilizing concatenation gradient to prove it.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Yiannis Kkkinos and Konstantinos Margaritis
Parallelism, Localization and Chain Gradient Tuning Combination for Fast Scalable Probabilistic Neural Network in information excavation
2012
Probe of probabilistic nervous web utilizing localisation and parallelization and a concatenation gradient tuning
3
A-
a?s
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
O ( N )
A-
a?s
A-
Artificial nervous web and information excavation
A-
A-
C utilizing MPI library
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
bayesian
Rules
A-
A-
Graphs and tabular arraies
18 ) Yiannis Kkkinos and Konstantinos Margaritis 2012 Parallelism, Localization and Chain Gradient Tuning Combination for Fast Scalable Probabilistic Neural Network in information excavation
[ 19 ] In this whole paper the writer is funny about acquiring high blood force per unit area informations from a infirmary information base. He is utilizing back extension algorithm in a multi-layered nervous web. In constructing determination the consequences offered are really attractive. With the aid of unreal intelligence approaches the hypothesis or activities of informations is shown along with that once unknown informations is exposed. This is all due to nervous webs that the writer is able to pattern irregular informations and complex construction along with that assorted other issues.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Mbuyi Mukendi Kafunda Katatayi Pierre, Mbuyi Badibanga Sreve, Mbuyi Mukendi Didier
Extraction cognition from high force per unit area informations patients
2012
Journal
Multi-layer nervous web
2
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
A-
a?s
Neural web utilizing supervised acquisition
Extraction of cognition signifier informations base with high blood force per unit area
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
BPN
regulations
Supervised
A-
Tables
19 ) Mbuyi Mukendi Kafunda Katatayi Pierre, Mbuyi Badibanga Sreve, Mbuyi Mukendi Didier 2012 Extraction cognition from high force per unit area informations patients
[ 20 ] In this article the writer focuses on one of major issue in nervous web. Neural web have been used for arrested development and categorization method in past. And the reading of their internal representation were really hard. Now a twenty-four hours, it is clear that for the extraction of the apprehensible representation from trained nervous web algorithm can be derived. The intent of which is to utilize for informations excavation applications. The work mentioned in this paper delivers a generalised process, which can be used for the jobs in bioinformatics. The consequences are truly impressive but the job is that of bring forthing a big sum of informations. Combination of algorithm with the nervous web for the intent of pull outing of information from the trained nervous web is the best solution, which produces high accurate informations along with that produces cognition find. The use of these methods leads to acceptance and high assurance.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Antoney Browne, Brain D. Hudson, David C. Whitley, Martyn G. Ford, Philip Picton
Execution and application of a flexible determination tree extraction algrothm to genomi job sphere
2004
Journal
Statistical and computational ideas.
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
A-
A-
a?s
Statistical anticipations and unreal intelligence
Genomic job sphere
a?s
Matlab/Netlab
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
Trepan Algorithm
Decision tree
A-
Traditional V new attack
Tables
20 ) Antoney Browne, Brain D. Hudson, David C. Whitley, Martyn G. Ford, Philip Picton 2004 Implementation and application of a flexible determination tree extraction algrothm to genomi job sphere
[ 21 ] The writer is covering with a major issue of anticipation for package quality. For deciding this hurdle he introduces an explainable nervous web theoretical account. This theoretical account consists upon a three layered provender frontward nervous web holding sigmoid in its inhumed units. The end product unit is holding individuality map and the theoretical account is trained consequently. From trained nervous web for the extraction of the regulations he make usage of the constellating familial algorithm. For the sensing of the mistake prone package the regulations extracted from the trained nervous web are gathered. And so the regulations are compared. The regulations of trained nervous web are compared with the regulation of foretelling consequences. The consequences show that trained nervous web regulations a spot accurate as comparison to that of foretelling consequences but foretelling consequences are more apprehensible.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Qi wang. Bo yu, jie zhu
Infusion Rules from Software Quality Prediction Model Based on
Nervous Network
2004
IEEE
Clustering familial and patterning methodological analysis
2
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
A-
a?s
Clustering and unreal intelligence
Software development attempts
A-
C linguistic communication
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
Fitness map and cross over mutant
Rules
Training informations
A-
Tables
21 ) Qi wang. Bo yu, jie zhu 2004 Extract Rules from Software Quality Prediction Model Based on Neural Network
[ 22 ] In informations excavation categorization is a cardinal topic to be focused. But covering with uncomplete study so categorization is an advanced topic. Traditional nervous web and other technique did non concentrate on the uncomplete study. So the writer presents a fresh attack known as extension nervous web attack to cover with the uncomplete study. This proposed attack is covering with the supervised information. After comparing the consequence of the planned attack with other attacks, it clearly shows that this attack has the benefit of high truth over other attacks.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Chao Lu, Xue- Wei Li, Hong-Bo Pan
Application of Extension Neural Network for Classification with Incomplete
Survey Data
2006
IEEE
Extension nervous web based on theoretical account of constellating
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Small sum
develop an
unsupervised larning algorithm of the proposed
extension nervous web,
A-
a?s
ANN and informations excavation technique
categorization with uncomplete study
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
Nervous web and categorization
Rules
supervised
New attack
Graph
22 ) Chao Lu, Xue- Wei Li, Hong-Bo Pan 2006 Application of Extension Neural Network for Classification with Incomplete Survey Data
[ 23 ] In this paper the writer is covering with different application of the information excavation and so selects the best method among them. First he finds out the concealed form utilizing different informations excavation attacks. Then harmonizing to their consequences he Kept based on Back extension neural web, the consequence of which is supplying improved security as comparison to the remainder of them.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
L. Wang and T. Z. Sui
Application of Data Mining Technology Based on
Nervous Network in the Technology
2007
IEEE
Back Propagation nervous web algorithm
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
A-
A-
a?s
Artificial nervous web
Engineering
A-
Matlab
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
A-
A-
Rules and determinations
Supervise/unsupervised
A-
Tables and graphs
23 ) L. Wang and T. Z. Sui 2007 Application of Data Mining Technology Based on Neural Network in the Technology
[ 24 ] The writer focuses on the diagnosing and mistake forecast methods of watercourse turbine which is wholly based on the familial and nervous web. For mistake diagnosing in watercourse turbine and in informations mining the familial and nervous web algorithm were introduces. By comparing the fresh attack to the traditional attack it is rather clear that has better public presentation and simple to plan. With the aid of proposed algorithm sharing turbine mistake diagnosing and regulations extraction which is based on familial and nervous web algorithm are bring forthing good consequences. The given system supply a good end product with better assurance along with that it has strong ability of mistake tolerant.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Qingling
A fresh attack of diagnosings stream turbine based on nervous web and familial algorithm
2008
IEEE
Novel attack based on nervous web and familial algorithm
2
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Large sum of memory
A-
a?s
Artificial nervous web with familial algortithm
Stream turbine
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
a?s
A-
Rules
A-
Traditional V novel attack
Tables
24 ) Qingling 2008 A fresh attack of diagnosings stream turbine based on nervous web and familial algorithm
[ 25 ] in this paper the writer focuses on the ANN and finds out different footings which are responsible for doing ANN system more intelligent. The writer is looking frontward and happening different ways for optimising ANN based on categorization methods. In this paper the writer makes usage of three standard data point for calculating the truth. The experimental consequences show that the system gave high truth.
Writer name
Paper name
Published day of the month
Paper description
Algorithm used
No of algorithm
No of inputs
Run clip efficiency
Guan Pinging
Exploitation of Minimum Risk System based on Artificial Neural Network
2011
IEEE
Artificial nervous web
1
A-
A-
Time complexness
Memory
Future thought
Man-made informations
Real clip
Tools for experiment
Experimental environment
Tree construction is used
Language for encoding
A-
Large sum of memory
A-
a?s
A-
Artificial nervous web
To cognize about ANN intelligence
A-
A-
Pruned web
Related model/algorithm
Based on
Type of informations
Algorithm type
Data presentation
a?s
A-
Rules and determinations
Supervise/unsupervised
A-
Tables
25 ) Guan Pinging 2011 Exploitation of Minimum Risk System based on Artificial Neural Network
