Feature Extraction for Image Classification and Analysis with Ant Colony Optimization Using Fuzzy Logic Approach

E se é verdade que a Cooperação Portuguesa tem apoiado, de forma regular, iniciativas con- sistentes para a construção da opinião pública, como o apoio a projectos da iniciativa

Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization. Modifications and additions to ant colony optimization to solve the

This approach is based on the optimization of the image interpolation formula using a single controlling parameter to preserve edges through the interpolation processS. Better

Consequently, the objective of the CVRP is to find a set of minimum cost routes to serve all the customers by satisfying the following constraints which are listed in

The great advantage over the use of exact methods is that ACO algorithm provides relatively good results by a comparatively low number of iterations, and is therefore able to find

The optimization method with contradictory test to check the fuzzy user preferences during the fuzzy AHP decision-making process, with consistency check and with derivation of

The techniques discussed in this paper are Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization Algorithm (BFOA),

The Fuzzy based Particle Swarm Optimization and Ant Colony Optimization (FPSO-ACO) technique is used to trim down the feature vector dimensionality and