BY,

BUBALAN.VPRATHEEBAN.RRAMPRASATH.C

GUIDED BY,

MRS. E.KODHAI, M.E, Ph.D(Pursuing)ASSOCIATE PROFESSOR

DEPT. OF INFORMATION TECHNOLOGY

Predicting and Optimizing the End Price of an Online Auction using Genetic-Fuzzy Approach

AGENDA

Introduction

Literature Survey

Problem Definition

Working Model

System Design

Module Description

Experimental Results

Discussion and Conclusion

Publication

References

Introduction

Popular mechanism in setting prices for internet users

Popular way of selling used items for scrap value and new items for

profit

Auction price prediction involves the uncertainty regarding the

bidding process

To predict the final prices of English auctions using real-world

online auction data, collected from eBay. Finally, optimize the

predicted values for maximum profit

Introduction (cont..)

Why Fuzzy Logic ?

Logic that deals mathematically with imprecise information

usually employed by humans

Humans can solve In-deterministic data

Computers can solve deterministic data

To make computers to handle the in-deterministic data

There also exists uncertainties in human behaviour while bidding

at auctions

Introduction (cont..)

Why Genetic Algorithm ?

Inspired by Darwin theory about evolution “Survival of fittest”

Search heuristic that mimics the process of natural evolution

Uses Bio Inspired operations( selection, mutation, crossover,

reproduction ) to evolve a solution to a problem

Particularly well suited for Large search space

Author’s Title Problem Techniques

Chin-Shien Lin et.al A Final price prediction model for English auctions: a neuro- fuzzy approach

Optimized results will not be produce if data is inaccurate

• Neural system• Regression• fuzzy logic

A.Azadeh et.al A new genetic algorithm approach for optimizing bidding strategy viewpoint of profit maximization of generation company

• best only for two players concern• should have more knowledge on rival's strategy

Genetic algorithm

Yun shi liu et.Al Real time prediction of closing price and duration Of B2B reverse auctions

We must employ real time information and prediction rules to forecast the behaviour of liveauctions.

Data mining

Rayid Ghani Price Prediction and Insurance for Online Auctions

deals specifically with online auctions, we believe that this is an interesting case study that applies to dynamic markets where theprice of the goods is variable and is affected by both internal andexternal factors that change over time.

Data Mining

Literature Survey

Problem Definition

The drawback of predicting the end price of an online auction in

existing system can be improved by the use of Genetic Fuzzy

approach. The proposed predicting system is a mathematical and

biological concept which takes eBay dataset to predict the end

price using Fuzzy logic and the predicted value is then optimized

using Genetic Algorithm.

Working Model

MODIFIED GENETIC ALGORITHM

1.Initiation of Parent population

2.Evaluation for Fittest

3.While Termination Criteria Not Satisfied

{

1.Selection Of child population(Rank Selection)

2.Apply Crossover(Single Point Crossover)

1.Evaluation

2.Replace the result if it is better than previously stored

3.Apply Mutation(flip)

1.Evaluation

2.Replace the result if it is better than previously stored

}

4.Go to Step 3 until termination criteria satisfies

Architecture Design

User Interface Design

Module Description

Registration Module

contains user information details, authentication of user

Filtering Module

Filters the auction data collected from e-Bay

Fuzzy Logic Module

contains fuzzy logic rules and processing codes for

prediction

Genetic Module

contains codes for algorithm for population generation ,

fitness evaluation ,selection, crossover and mutation

Experimental Results

Experimental Results(cont..)

Comparison between the results of FL and GA

Pri

ce

Bid Price

Discussion and Conclusion

Performance Comparison b/w Neuro Fuzzy ,Fuzzy & Genetic Fuzzy Approach

Performance of the proposed system is calculated using Mean square error

method

Yi is the actual price and Y^I is the Predicted or Optimized Price and n

represents Observation

Based on this method the average error of the current system is 0.02181 while

the existing system 0.0735

Discussion and Conclusion(cont..)

Genetic Fuzzy performs the best no matter in the training data sets or

testing data sets.

To the better prediction accuracy

Genetic Fuzzy system also provides the knowledge base obtained from

the data set which describes the delicate relationship among the

variables.

Publication

PAPER TITLE

Predicting and Optimizing the End Price of an Online Auction using Genetic -

Fuzzy Approach

JOURNAL NAME

International Journal Of Advanced And Innovative Research

ISSUE

Vol. 2 Issue 2

DATE

Febraury, 2013

PAGE

145 to 150

ISSUE ISSN

2278-7844

References

[1] Chin-Shien Lin, Shihyu Chou, Shih-Min Weng, Yu-Chen Hsieh, “A Final Price Prediction Model for English Auctions — A Neuro-Fuzzy Approach”, 2011.

[2] Rechenberg, Ingo. “Evolutionsstrategie”. Stuttgart: Holzmann-Froboog.,1973, ISBN 3-7728-0373-3.

[3] Srinivas. M and Patnaik. L, "Adaptive probabilities of crossover and mutation in genetic algorithms," IEEE Transactions on System, Man and Cybernetics, vol.24, no.4, pp.656–667, 1994.

[4] “A Genetic Algorithm Tutorial”, Darrell Whitley, Computer Science Department, Colorado State University, Fort Collins, CO 80523.

[5] Rayid Ghani, Hillery Simmons, “Predicting the End-Price of Online Auctions”, 2004.

References (cont..)

[6] Kim, Yongseog, “An Optimal Auction Infrastructure Design: An Agent-based Simulation Approach,” Proceedings of the Tenth Americas Conference on Information System, New York, 2004.

[7] Lucking-Reiley, D., “Auctions on the Internet: What’s Being Auctioned, and How?,” Journal of Industrial Economics, 2000, 48(3).

[8] Pinker, E.J., Seidmann, A. & Vakrat, Y. “Managing Online Auctions: Current Business and Research Issues,” Management Science, 2003, 49(11), 1457–1484.

[9] Karl Nygren, “Stock Prediction – A Neural Network Approach”, March 2004.

[10] Fei Dong, Sol M. Shatz, Haiping Xu, “An Empirical Evaluation on the Relationship between Final Auction Price and Shilling Activity in Online Auctions”, Jan 2011.

THANK YOU !