In Bioinformatics, sequence analysis is the basic important concept that provides information for structural and functional analysis. Multiple Sequence Alignment (MSA) is a keystone problem in the sequence analysis that is used for constructing phylogenetic tree, finding motif, gene expression,...

In this paper a predictor model using Legendre Neural Network is proposed for one day ahead prediction of financial time series data. The Legendre Neural Network (LENN) is a single layer structure that possess faster convergence rate and reduced computational complexity by increasing the...

This paper demonstrates a novel local search approach based on an adaptive (time variant) search space index improving the exploration ability as well as diversity in multi-objective Particle Swarm Optimization. The novel strategy searches for the neighbourhood particles in a range which...

A machine vision system with single monochrome CCD camera and backlight was developed for tool positioning and verification. While evaluating the performance of the developed vision system, the experiments showed that the output of machine vision system was not comparable to the output of...

Since two of the most important disadvantages of the classical nonlinear regression methods, such as Levenberg-Marquardt (LM), are to calculate error derivative function and use an initial point to get the results, PSO algorithm, which lies in the category of population based meta-heuristic...

Classical Particle Swarm Optimization (PSO) that has been attempted for the solution of complex constrained portfolio optimization problem in finance, despite its noteworthy track record, suffers from the perils of getting trapped in local optima yielding inferior solutions and unrealistic time...

Bioinformatics has grown very quickly for the last 20 years, and it will grow even faster in the future. One of the long-standing open challenges in bioinformatics is biomarker identification and cancer diagnosis from gene expression. In this paper, the authors propose a novel hybrid...

The paper contains an extensive experimental study which focuses on a major idea on Target Optimization (TO) prior to the training process of artificial machines. Generally, during training process of an artificial machine, output is computed from two important parameters i.e. input and target....

Traveling salesman problem (TSP) is one well-known NP-Complete problem. The objective is to search the optimal Hamiltonian circuit (OHC) in a tourist map. The particle swarm optimization (PSO) integrated with the four vertices and three lines inequality is introduced to detect the OHC or...

Multilevel thresholding is a popular image segmentation technique. However, computational complexity of multilevel thresholding increases very rapidly with increasing number of thresholds. Metaheuristic algorithms are applied to reduce computational complexity of multilevel thresholding. A new...