In this paper, we will proposed a hybrid method to generate fuzzy membership function automatically. Particle Swarm Optimization (PSO) is used as optimized algorithm, supplement the performance of fuzzy system. The PSO is able to generate an optimal set of parameter for the membership functions automatic adjustment. Fuzzy control system that automatically backs up a truck to a specified point o...

This paper presents a new improved from particle swarm optimization to tune optimal rule-base of a Fuzzy Proportional Integral Differential (FPID) which leads to damp low frequency oscillation following disturbances in power systems, while called Particle Swarm Optimization with Time Variant Acceleration Coefficient (PSO-TVAC). Thus, extraction of an appropriate set of rules or selection of an ...

In fuzzy logic controllers (FLCs), optimal performance can be defined as performance that minimizes the deviation (error term) between the decisions of the fuzzy logic systems and the decisions of experts. A range of approaches – such as genetic algorithms (GA), particle swarm optimization (PSO), artificial neural networks (ANN), and adaptive network based fuzzy inference systems (ANFIS) – can ...

This paper proposes a novel particle swarm optimization (PSO) algorithm based fuzzy logic controller (FLC) for improving the performance of automatic solid-state transfer switch (SSTS) with respect to time. The proposed technique generates adaptive membership functions (MFs) voltage error and rate change input output on fitness function formulated by PSO. An optimal PSO-based FLC (PSOF) is furt...

Integration and diversity of IOT terminals their applicable programs make them more vulnerable to many intrusive attacks. Thus, designing an intrusion detection model that ensures the security, integrity, reliability is vital. Traditional technology has disadvantages low rates weak scalability cannot adapt complicated changing environment Internet Things. Hence, one most widely used traditional...

As we all know, the parameter optimization of Mamdani model has a defect of easily falling into local optimum. To solve this problem, we propose a new algorithm by constructing Mamdani Fuzzy neural networks. This new scheme uses fuzzy clustering based on particle swarm optimization (PSO) algorithm to determine initial parameter of Mamdani Fuzzy neural networks. Then it adopts PSO algorithm to o...

this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...

Accurate medical diagnosis requires a segmentation of large number of medical images. The automatic segmentation is still challenging because of low image contrast and ill-defined boundaries. Image segmentation refers to the process that partitions an image into mutually exclusive regions that cover the image. Among the various image segmentation techniques, traditional image segmentation metho...

The basic theories, development and applications of particle swarm optimization and genetic algorithm are introducedd.Some models of improved PSO algorithms are outlined. Characteristics of PSO and GA are compared. Two methods of hybrid of PSO and GA at present was summarized:hybrid with two algorithms entirely or with only a few steps ,and illustrated with flowchart.Limitation of two methods o...