Swarm intelligence is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment cause coherent functional global patterns to emerge. Although the swarm algorithms have exhibited good performance across a wide range of application problems, it is difficult to analyze the convergence. In this paper, we...

Compositions measurement is a vitally critical issue for the modelling and control of distillation process. The product compositions of distillation columns are traditionally measured using indirect techniques via inferring tray compositions from its temperature or by using an online analyser. These techniques were reported as inefficient and relatively slow methods. In this paper, an alternati...

A recently proposed swarm intelligence technique for Fuzzy Cognitive Map learning is described. The technique employs the Particle Swarm Optimization algorithm to minimize a proper objective function, whose global minimizers correspond to suboptimal weight matrices of the Fuzzy Cognitive Map. New instances of an industrial test problem are studied, justifying the usefulness of the technique as ...

This paper introduces a novel approach deploying the mechanism of ‘attention’ by adapting a swarm intelligence algorithm – Stochastic Diffusion Search – to selectively attend to detailed areas of a digital canvas. Once the attention of the swarm is drawn to a certain line within the canvas, the capability of another swarm intelligence algorithm – Particle Swarm Intelligence – is used to produce...

This article presents a hybrid evolutionary algorithm (PSABC) based on Artificial Bee Colony (ABC) and particle swarm optimization (PSO). Both of the algorithms are co-operative, population-based global search swarm intelligence met heuristics. The core of this algorithm is using PSO to optimize the fitness value of population in ABC. For Evaluation purpose, the proposed algorithm is tested on ...

A technique for Fuzzy Cognitive Maps learning, which is based on the minimization of a properly defined objective function using the Particle Swarm Optimization algorithm, is presented. The workings of the technique are illustrated on an industrial process control problem. The obtained results support the claim that swarm intelligence algorithms can be a valuable tool for Fuzzy Cognitive Maps l...

This paper discusses how concepts derived from nature can be applied successfully to improve the performance of the rule mining process. These concepts are derived from swarm intelligence and behavior of frogs. Swarm Intelligence (SI) is the property of a system whereby the collective behavior of agents interacting locally with their environment causes coherent functional global patterns to eme...

Swarm intelligence deals with natural and arti cial systems composed of many individuals that coordinate using decentralized control and self-organization [1, 2, 5]. The main focus of swarm intelligence research is on the collective behaviour that results from local interactions of individuals with each other and with their environment. There are many examples of natural systems that are studie...

This review paper sets out to explore the question of how future complex engineered systems based upon the swarm intelligence paradigm could be assured for dependability. The paper introduces the new concept of ‘swarm engineering’: a fusion of dependable systems engineering and swarm intelligence. The paper reviews the disciplines and processes conventionally employed to assure the dependabilit...