this study investigates the oil extraction from pistacia khinjuk by the application of enzyme.artificial neural network (ann) and adaptive neuro fuzzy inference system (anfis) were applied formodeling and prediction of oil extraction yield. 16 data points were collected and the ann was trained with onehidden layer using various numbers of neurons. a two-layered ann provides the best results, us...

This paper presents a new method, which combines sharing and a fuzzy clustering technique to improve the performance of genetic algorithms in multimodal function optimization. This approach permits some limitations of the traditional sharing scheme to be overcome. Without using any prior information, it allows both location and maintenance of niches. Computer simulations show good performance f...

This paper presents an improved particle swarm optimizer (PSO) for solving multimodal optimization problems with problem-specific constraints and mixed variables. The standard PSO is extended by employing a comprehensive learning strategy, different particle updating approaches, and a feasibility-based rule method. The experiment results show the algorithm located the global optima in all teste...

This paper presents a novel adaptive multiobjective particle swarm optimization algorithm and with adaptive multi-objective particle swarm algorithm for solving objective constrained optimization problems, in which Pareto non-dominated ranking, tournament selection, crowding distance method were introduced, simultaneously the rate of crowding distance changing were integrated into the algorithm...

The authors designed an automated framework to segment tumors with various image sequences like T1, T2, and post-processed MRI multimodal images. Contrast-limited adaptive histogram equalization method is used for preprocessing images enhance the intensity level view tumor part clearly. With combination of kernel possibilistic c means clustering particle swarm optimization technique, a segmente...

Computing equilibria of multiplayer noncooperative normal form games is a difficult computational task. In games having more equilibria mathematical algorithms are not capable to detect all equilibria at a time. Evolutionary algorithms are powerful search tools for solving difficult optimization problems. It is shown how an evolutionary algorithm designed for multimodal optimization can be used...