Particle Swarm Optimization and Artificial Bee Colony Approaches to Optimize of Single Input-output Fuzzy Membership Functions
نویسندگان
چکیده
Determination of the fuzzy membership functions in a given fuzzy logic system is the key factor for resulting in the best performance. Thus, in this study, particle swarm optimization (PSO) and artificial bee colony (ABC), relatively new member of swarm intelligence, are used to adjust the shape of fuzzy membership functions, respectively. Proposed methods have been implemented and compared for a single input-output (SI-O) fuzzy system. The obtained results show that using PSO and ABC methods are capable and effective to find optimal values of fuzzy membership functions in a reasonable time.
منابع مشابه
OPTIMIZATION OF SKELETAL STRUCTURAL USING ARTIFICIAL BEE COLONY ALGORITHM
Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...
متن کاملIntegrated Well Placement and Completion Optimization using Heuristic Algorithms: A Case Study of an Iranian Carbonate Formation
Determination of optimum location for drilling a new well not only requires engineering judgments but also consumes excessive computational time. Additionally, availability of many physical constraints such as the well length, trajectory, and completion type and the numerous affecting parameters including, well type, well numbers, well-control variables prompt that the optimization approaches b...
متن کاملOptimization of fuzzy membership functions via PSO and GA with application to quad rotor
Quad rotor is a renowned underactuated Unmanned Aerial Vehicle (UAV) with widespread military and civilian applications. Despite its simple structure, the vehicle suffers from inherent instability. Therefore, control designers always face formidable challenge in stabilization and control goal. In this paper fuzzy membership functions of the quad rotor’s fuzzy controllers are optimized using nat...
متن کاملBQIABC: A new Quantum-Inspired Artificial Bee Colony Algorithm for Binary Optimization Problems
Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper a new binary version of the ABC algorithm inspired by quantum computing, c...
متن کاملFinding the Optimal Path to Restoration Loads of Power Distribution Network by Hybrid GA-BCO Algorithms Under Fault and Fuzzy Objective Functions with Load Variations
In this paper proposes a fuzzy multi-objective hybrid Genetic and Bee colony optimization algorithm(GA-BCO) to find the optimal restoration of loads of power distribution network under fault.Restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. To improve the efficiency of restoration and facilitate theactivity...
متن کامل