The Hunch Factor: Exploration into Using Fuzzy Logic to Model Intuition in Particle Swarm Optimization
نویسنده
چکیده
Particle Swarm Optimization (PSO) is a powerful biologybased optimization search strategy. This paper explores the addition of intuition into the PSO algorithm to improve the speed and number of iterations required to find solutions to the problem. This intuition will be modeled using a fuzzy variable called the Hunch Factor. It will act as memory for the system and influence the choices of the algorithm. Thus, allowing the algorithm to make more human-like decisions. This paper is an early exploration into the hunch factor via several experiments of the hunch factor with a simple optimization problem.
منابع مشابه
A New Approach to Measuring Cementation Factor by Using an Intelligent System
Cementation factor is a critical parameter, which affects water saturation calculation. In carbonate rocks, due to the sensitivity of this parameter to pore type, water saturation estimation has associated with high inaccuracy. Hence developing a reliable mathematical strategy to determine these properties accurately is of crucial importance. To this end, genetic algorithm pattern search is emp...
متن کاملFrequency Control of an Islanded Microgrid based on Intelligent Control of Demand Response using Fuzzy Logic and Particle Swarm Optimization (PSO) Algorithm
Due to the increasing penetration of renewable energies in the power system, the frequency control problem has attracted more attention, while the traditional control methods are not capable of regulating the frequency and securing the stability of the system. In smart grids, demand response as the frequency control tool reduces the dependence on spinning reserve and high cost controllers. In a...
متن کاملAN OPTIMAL FUZZY SLIDING MODE CONTROLLER DESIGN BASED ON PARTICLE SWARM OPTIMIZATION AND USING SCALAR SIGN FUNCTION
This paper addresses the problems caused by an inappropriate selection of sliding surface parameters in fuzzy sliding mode controllers via an optimization approach. In particular, the proposed method employs the parallel distributed compensator scheme to design the state feedback based control law. The controller gains are determined in offline mode via a linear quadratic regular. The particle ...
متن کاملOptimal intelligent control for glucose regulation
This paper introduces a novel control methodology based on fuzzy controller for a glucose-insulin regulatory system of type I diabetes patient. First, in order to incorporate knowledge about patient treatment, a fuzzy logic controller is employed for regulating the gains of the basis Proportional-Integral (PI) as a self-tuning controller. Then, to overcome the key drawback of fuzzy logic contro...
متن کاملAdaptive particularly tunable fuzzy particle swarm optimization algorithm
Particle Swarm Optimization (PSO) is a metaheuristic optimization algorithm that owes much of its allure to its simplicity and its high effectiveness in solving sophisticated optimization problems. However, since the performance of the standard PSO is prone to being trapped in local extrema, abundant variants of PSO have been proposed by far. For instance, Fuzzy Adaptive PSO (FAPSO) algorithms ...
متن کامل