Computer-Aided Design and Applications is an international journal on the applications of CAD CAM. It publishes papers in general domain plus emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, data mining, internet, education, genetic algorithms engines. The aimed at all developers users technology to ptovide solutions for various stages design manufacturing. about technol...

there are instances in which it is desirable to determine relationships among fruit physical attributes. for example, fruits are often graded on the basis of size and projected area, but it may be more suitable and/or economical to develop a machine which grades by mass. therefore, a relationship between mass and dimensions or projected areas and/ or volume of fruits is needed. various grad...

fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. in this paper, a modified method based on the comprehensive learning particle swarm optimization (clpso) is proposed for pixel classification in hsi color space by selecting a fuzzy classification system with minimum number of fuzzy rules and minimum number of incorr...

in this paper, we propose a new gene selection algorithm based on shuffled frog leaping algorithm that is called sfla-fs. the proposed algorithm is used for improving cancer classification accuracy. most of the biological datasets such as cancer datasets have a large number of genes and few samples. however, most of these genes are not usable in some tasks for example in cancer classification. ...

In today world of internet, it is important to feedback the users based on what they demand. Moreover, one of the important tasks in data mining is classification. Today, there are several classification techniques in order to solve the classification problems like Genetic Algorithm, Decision Tree, Bayesian and others. In this article, it is attempted to classify researchers to “Expert” and “No...

This paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. The classification performance andinterpretability are of major importance in these systems. In this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). Ourapproach uses a punish...