rainfall-runoff modeling is most important component in the water resource management of river basins. the successful application of a conceptual rainfall-runoff model depends on how well it is calibrated. the degree of difficulty in solving the global optimization method is generally dependent on the dimensionality of the model and certain of the characteristics of object function. the purpose...

Cryptanalysis with Computational Intelligence has gained much interest in recent years. This paper presents an approach for breaking the key used in Simplified-Data Encryption Standard (S-DES) using Genetic algorithm (GA), Particle Swarm Optimization (PSO) and a novel approach called Genetic Swarm Optimization (GSO) obtained by combining the effectiveness of GA and PSO. Ciphertext-only attack i...

Data mining technology has emerged as a means of discovering hidden patterns and trends among large volumes of data and thus it can be considered as an important step in the knowledge discovery (KDD) process. In the area of data mining the task of Association rule (AR) mining is to discover interesting relations among various items in the database. One of the subfield of artificial intelligence...

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each part...

According to the intelligent behavior of social population, the centroid of the individual best of particle swarm is firstly introduced in particle swarm optimization (PSO) model to enhance inter-particle cooperation and information sharing capabilities, then combining the mechanism of population migration algorithm (PMA), a novel PSO algorithm with adaptive space mutation (PMCPSO) is proposed ...

In this paper, particle trajectories of PSO algorithms in the first iteration are studied. We will prove that many particles leave the search space at the beginning of the optimization process when solving problems with boundary constraints in high-dimensional search spaces. Three different velocity initialization strategies will be investigated, but even initializing velocities to zero cannot ...

Abstract— The aim of this paper is to study the tuning of a PID controller using swarm optimization techniques. In this paper, comparative performance of PSO and BF-PSO based PID controller is analyzed. PSO algorithm converges rapidly during the initial stages of a global search, but around global optimum, the search process slows down. In order to overcome this problem and to further enhance t...

In this paper, a novel technique is developed by hybridizing Bacterial Foraging Optimization technique in conjunction with Particle Swarm Optimization and is applied to the expressions developed by M.Kara to calculate accurately the desired resonant frequency of rectangular microstrip antenna of any dimension and of any substrate thickness. Index Terms Bacterial Foraging Optimization (BFO), Par...

Particle swarm optimization is an efficient population based algorithm used to solve real valued and nonlinear continuous optimization problems. To resolve binary optimization problems with PSO, binary particle swarm optimization (BPSO) has been developed. In this paper, optimum design of plates using BPSO is presented. The objective function aims at finding the optimum weight of plates with th...

This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. The proposed new algorithm moves particles towards nearby particles of higher fitness, instead of attracting each particle towards just the best position discovered so far by any particle. This is accomplished by usin...