The evaluation of solutions is an important phase in power distribution system planning (PDSP) which allows issues such as quality of supply, cost, social service and environmental implications to be considered and usually involves the judgments of a group of experts. The planning problem is thus suitable for the multi-criteria group decision-making (MCGDM) method. The evaluation process and ev...

The min-max modular support vector machine (M-SVM) was proposed for dealing with large-scale pattern classification problems. M-SVM divides training data to several sub-sets, and combine them to a series of independent sub-problems, which can be learned in a parallel way. In this paper, we explore the use of the geometric relation among training data in task decomposition. The experimental resu...

The development of microarray technology has motivated interest of its use in clinical diagnosis of tumor and drug discovery. However the accurate classification of tumor by selecting the tumor-related genes from thousands of genes is a difficulty task due to the large number of redundant genes. Therefore, we propose a novel hybrid approach which combines rough set theory with support vector ma...

Support vector machine (SVM) is sensitive to the outliers, which reduces its generalization ability. This paper presents a novel support vector regression (SVR) together with fuzzification theory, inconsistency matrix and neighbors match operator to address this critical issue. Fuzzification method is exploited to assign similarities on the input space and on the output response to each pair of...

In this paper, we propose a new rough set classifier induced from partially uncertain decision system. The proposed classifier aims at simplifying the uncertain decision system and generating more significant belief decision rules for classification process. The uncertainty is reperesented by the belief functions and exists only in the decision attribute and not in condition attribute values.

The quality of the natural environment has become one of the primary concerns in present society. In Canada, we have been asked to take on the “One Tonne Challenge” to reduce personal household emissions by 1 tonne. However, very little has been done to illuminate the various connections between our household purchases and the effect they can have on the quality of our health and environment. S...

This paper proposes a decision support system which integrates the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the composite weights of importance of the attributes. Using fuzzy set theory the qualitative attributes are converted into the quantitative attributes. Based on this model, a decision support system AGVSEL is ...

Recently, there has been a growing interest in the data mining area, where the objective is the discovery of knowledge that is correct, comprehensible, easily interpreted, and can be understood and used by users. This paper addresses the issue by facilitating the automatic construction of a decision support system by utilizing data mining techniques. In this research a system that extracts rule...

Soft set theory is a newly emerging tool to deal with uncertain problems and has been studied by scholars in theory and practice. This paper proposes the concept of bijective soft set and some of its operations such as the restricted AND and the relaxed AND operations on a bijective soft set, dependency between two bijective soft sets, bijective soft decision system, significance of bijective s...

We explore how virtual examples (artificially created examples) improve performance of text classification with Support Vector Machines (SVMs). We propose techniques to create virtual examples for text classification based on the assumption that the category of a document is unchanged even if a small number of words are added or deleted. We evaluate the proposed methods by Reuters-21758 test se...