This report presents a study of integrating particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the social learning of self-organized groups and their collective searching behavior in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social learning for a dynamic environment. The research provi...

Abstract Several studies exist in the literature that utilized metaheuristics and nature-inspired algorithms to solve engineering problems. Particle Swarm Optimization (PSO) is a well-known algorithm has been used for different optimization problems due its simplicity ability find near-optimal solutions. However, PSO suffers from problem of balancing between global search local abilities when a...

In this paper, we proposed a multi-objective Pareto based particle swarm optimization (MOPPSO) to minimize the architectural complexity and maximize the classification accuracy of a polynomial neural network (PNN). To support this, we provide an extensive review of the literature on multi-objective particle swarm optimization and PNN. Classification using PNN can be considered as a multi-object...

Swarm Intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment causing coherent functional global patterns to emerge. The intelligence emerges from a chaotic balance between individuality and sociality. The chaotic balances are a characteristic feature of the complex system. Thi...

Artificial fish swarm algorithm (AFSA) assisted multi-user detection (MUD) is proposed for the receive-antenna-diversity-aided multi-carrier code-division multiple-access (MC-CDMA) systems in frequency selective fading channel. Due to the receive-diversity, the signals received at the different antennas are faded independently, resulting in an independent objective function for each antenna. To...

Unmanned Aerial Vehicle (UAV) or drone, is an evolving technology in today's market with enormous number of applications. Mini UAVs are developed order to compensate the performance constraints imposed by larger during emergency situations. Multiple mini autonomous require communication and coordination for ubiquitous coverage relaying deployment. Multi-UAV swarm optimization required reliable ...

This paper introduces an effective method by combining the multi-objective technique with bird swarm algorithm (BSA) to obtain a new called MBSA. The MBSA obtains some of different non-dominated techniques that maintain variety amongst optimal solutions. To verify and evaluate effectiveness MBSA, collections constrained, unconstrained, engineering problems are measured. These have various Paret...