Advances in Information Mining

Number 1, 2010

1-7
FUZZY MULTI-OBJECTIVE MULTI-INDEX TRANSPORTATION PROBLEM

Authors: Lohgaonkar M.H., Bajaj V.H., Jadhav V.A., Patwari M.B

Abstract

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Number of views: 532

The aim of this paper is to present a fuzzy multi-objective multi-index transportation problem and develop multi-objective multi-index fuzzy programming model. This model cannot only satisfy more of the actual requirements of the integral system but is also more flexible than conventional transportation problems. Furthermore, it can offer more information to the decision maker (DM) for reference, and then it can raise the quality for decision-making. This paper, we use a special type of linear and non-linear membership functions to solve the multi-objective multi-index transportation problem. It gives an optimal compromise solution.

8-12
A NEW FUZZY MADM APPROACH USED FOR FINITE SELECTION PROBLEM

Authors: Muley A.A. , Bajaj V.H

Abstract

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Number of views: 529

This paper proposes a new approach to product configuration by applying the theory of Fuzzy Multiple Attribute Decision Making (FMADM), which focuses on uncertain and fuzzy requirements the customer, submits to the product supplier. The proposed method can be used in e-commerce websites, with which it is easy for customers to get his preferred product according to the utility value with respect to all attributes. The main concern of this paper, in which requirements the customer submitted to the configuration of television is vague. Further verify the validity and the feasibility of the proposed method compared with Weighted Product Method (WPM). Finally, the television is taken as an example to demonstrate the proposed methods.

13-17
ANT BASED RULE MINING WITH PARALLEL FUZZY CLUSTER

Authors: Sankar K., Krishnamoorthy K

Abstract

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Number of views: 540

Ant-based techniques, in the computer sciences, are designed those who take biological inspirations on the behavior of these social insects. Data clustering techniques are classification algorithms that have a wide range of applications, from Biology to Image processing and Data presentation. Since real life ants do perform clustering and sorting of objects among their many activities, we expect that an study of ant colonies can provide new insights for clustering techniques. The aim of clustering is to separate a set of data points into self-similar groups such that the points that belong to the same group are more similar than the points belonging to different groups. Each group is called a cluster. Data may be clustered using an iterative version of the Fuzzy C means (FCM) algorithm, but the draw back of FCM algorithm is that it is very sensitive to cluster center initialization because the search is based on the hill climbing heuristic. The ant based algorithm provides a relevant partition of data without any knowledge of the initial cluster centers. In the past researchers have used ant based algorithms which are based on stochastic principles coupled with the k-means algorithm. The proposed system in this work use the Fuzzy C means algorithm as the deterministic algorithm for ant optimization. The proposed model is used after reformulation and the partitions obtained from the ant based algorithm were better optimized than those from randomly initialized hard C Means. The proposed technique executes the ant fuzzy in parallel for multiple clusters. This would enhance the speed and accuracy of cluster formation for the required system problem.

18-22
DATA MINING- A MATHEMATICAL REALIZATION AND CRYPTIC APPLICATION USING VARIABLE KEY

Authors: Chakrabarti P

Abstract

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Number of views: 548

In this paper we have depicted the various mathematical models based on the themes on data mining. The numerical representations of regression and linear models have been explained. We have also shown the prediction of datum in the light of statistical approaches namely probabilistic approach, data estimation and dispersion theory. The paper also deals with the efficient generation of shared keys required for direct communication among co-processors without active participation of server. Hence minimization of time-complexity, proper utilization of resource as well as environment for parallel computing can be achieved with higher throughput in secured fashion. The techniques involved are cryptic methods based support analysis, confidence rule, resource mining, sequence mining and feature extraction. A new approach towards realizing variability concept of key in Wide â€“ Mouth Frog Protocol, Yahalom Protocol and SKEY Protocol has been depicted in this context.