In this paper, we intend to study the synthesis of the multibeam arrays. The synthesis implementation’s method for this type of arrays permits to approach the appropriated radiance’s diagram. An adaptive particle swarm optimization algorithm (APSO) is proposed to synthesis multibeam antenna arrays. The problem is formulated and solved by means of the proposed algorithm. The examples are simulat...

The coverage problem is a crucial issue in wireless sensor networks (WSN); however, a high coverage rate ensures a high quality of service in WSN. This paper presents control of the coverage problem optimization via the adaptive particle swarm optimization (APSO) approach. The proper selection of inertia weight of APSO gives balance between global and local searching, and the research of this p...

This research paper presents a new evolutionary optimization model based on the particle swarm optimization (PSO) algorithm that incorporates the flocking behavior of a spider. The search space is divided into several segments like the net of a spider. The social information sharing among the swarms are made strong and adaptive. The main focus is on the fitness of the swarms adjusting to the le...

One of the most important and effort intensive activity of the entire software development process is software testing. The effort involved chiefly increases because of the need to obtain optimal test data out of the entire search space of the problem under testing. Software test data generation is one area that has seen tremendous research in terms of automation and optimization. Generating or...

Metaheuristic algorithm is one of the most popular methods in solving many optimization problems. This paper presents a new hybrid approach comprising of two natures inspired metaheuristic algorithms i.e. Cuckoo Search (CS) and Accelerated Particle Swarm Optimization (APSO) for training Artificial Neural Networks (ANN). In order to increase the probability of the egg’s survival, the cuckoo bird...

Purpose – In this paper, a new method to improve the performance of particle swarm optimization is proposed. Design/methodology/approach – This paper introduces hypothesis testing to determine whether the particles trap into the local minimum or not, then special re-initialization was proposed, finally, some famous benchmarks and constrained engineering optimization problems were used to test t...

Data clustering is a recognized data analysis method in data mining whereas K-Means is the well known partitional clustering method, possessing pleasant features. We observed that, K-Means and other partitional clustering techniques suffer from several limitations such as initial cluster centre selection, preknowledge of number of clusters, dead unit problem, multiple cluster membership and pre...

In recent years, evolutionary optimization (EO) techniques have attracted considerable attention in the design of electromagnetic systems of increasing complexity. This paper presents a comparison between two optimization algorithms for the synthesis of uniform linear and planar antennas arrays, the first one is an adaptive particle swarm optimization (APSO) where the inertia weight and acceler...

To address the problems of 5G network planning and optimization, a user time delay prediction model based on BiLSTM neural optimized by APSO-SD is proposed. First, channel generative ray-tracing statistical constructed to obtain large amount data, ray data feature three-dimensional stereo mapping proposed for input extraction. Then, an adaptive particle swarm optimization algorithm search pertu...

This paper presents the optimal fuzzy controller design for load frequency control (LFC) of two area power system using Adaptive Particle Swarm Optimization (APSO). Firstly, the controller is designed according to Fuzzy Logic rules such that the systems are fundamentally robust. Secondly, the Fuzzy Logic controller (FLC) used earlier was optimized with PSO so as to obtain optimal adjustment of ...