The heuristics herein presented are modified versions of the artificial fish swarm algorithm for global optimization. The new ideas aim to improve solution accuracy and reduce computational costs, in particular the number of function evaluations. The modifications also focus on special point movements, such as the random, search and the leap movements. A local search is applied to refine promis...

Firstly, this paper describes how the histogram analysis method pre-processes the images to be segmented. Then is makes a detailed analysis of the working principles and behaviour pattern of basic artificial fish swarm algorithm (AFSA); dissects the defects of AFSA in principle and proposes an improved AFSA with global convergence. Finally, it presents the main steps of image threshold segmenta...

Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality g...

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded ...

Non-orthogonal multiple access (NOMA) technology can greatly improve user and spectral efficiency. This paper considers the power allocation optimization problem of a two-user mobile NOMA communication system. Firstly, system model is established. Then, we analyze outage probability (OP) relationship between OP performance coefficient. Finally, objective function established, algorithm employin...

Particle swarm optimization (PSO) is a population-based stochastic optimization originating from artificial life and evolutionary computation. PSO is motivated by the social behavior of organisms, such as bird flocking, fish schooling and human social relations. Its properties of low constraint on the continuity of objective function and ability of adapting to the dynamic environment make PSO b...

Swarm intelligence via its infamous struggle to identify a suitable balance between exploration and exploitation phases, provides a valuable mean to approach artificial creativity. This work deploys two swarm intelligence algorithms, one simulating the behaviour of birds flocking and fish schooling (Particle Swarm Optimisation) and the other mimicking the behaviour of ants foraging (Stochastic ...

Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. In particular, the discipline focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. Examples of systems studied by swarm intelligenc...