Particle swarm optimization (PSO) is a population based statistical optimization technique which is inspired by social behavior of bird flocking or fish schooling. The main weakness of PSO especially in multimodal problems is trapping in local minima. Recently a learning automata based PSO called PSO-LA to improve the performance of PSO has been reported. PSO-LA uses one learning automaton for ...

We consider real trigonometric polynomial Bernoulli equations of the form A(θ)y′=B1(θ)+Bn(θ)yn where n≥2, with A,B1,Bn being polynomials degree at most μ≥1 in variables θ and Bn(θ)≢0. also A(θ)yn−1y′=B0(θ)+Bn(θ)yn A,B0,Bn variable For first equation, we show that when n≥4, it has 3 solutions n is even 5 odd. second n≥3, odd even. provide two types mentioned above maximum number achieved. The pr...

This paper presents a designing an optimal adaptive controller for tracking down the control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been used to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using a logic is proposed to increase the c...

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other hand, basic PSO is more appropriate to pro...

Let Θ(G) denote the Shannon capacity of a graph G. We give an elementary proof equivalence, for any graphs G and H, inequalities Θ(G⊔H)>Θ(G)+Θ(H) Θ(G⊠H)>Θ(G)Θ(H). This was shown independently by Wigderson Zuiddam (2022) using Kadison–Dubois duality Axiom choice.

This paper investigates into hybridization between PSO and self-adaptive evolutionary programming techniques for solving economic dispatch (ED) problem with non-smooth cost curves where conventional gradient based methods are in-applicable. The convergence capability of evolutionary programming technique is enhanced with hybridization of self-adaptive evolutionary programming technique with PSO...

this paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (pso) algorithm. pso algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ise) as a performance criteria. in this paper, an improved pso using logic is proposed to increase the convergenc...