This paper presents a novel fuzzy particle swarm optimization with cross-mutated operation (FPSOCM), where a fuzzy logic system developed based on the knowledge of swarm intelligent is proposed to determine the inertia weight for the swarm movement of particle swarm optimization (PSO) and the control parameter of a newly introduced cross-mutated operation. Hence, the inertia weight of the PSO c...

Leakage of oil from pipelines and oil tankers into seas and oceans is ecologically important and can have significant social and economic impacts on the environment. An early detection of deliberate or accidental oil spills can reduce serious hazards that may threaten coastal residents and help identify pollutants. Iran has been surrounded by seas from the north and the south and they provide u...

Artificial intelligence methods such as fuzzy logic and particle swarm optimization (PSO) have been applied to maximum power point tracking (MPPT) for solar panels. The P-V curve of a panel exhibits multiple peaks under partial shading condition (PSC) when all modules do not receive the same irradiation. Although conventional PSO has shown perform well uniform insolation, it is often unable fin...

Particle Swarm Optimization (PSO) is a swarm intelligence optimization method inspired from birds’ flocking or fish schooling. Many improved versions of PSO are reported in literature, including some by the authors. Original as well as improved versions of PSO have proven their applicability to various fields like science, engineering and industries. Economic dispatch (ED) problem is one of the...

Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to r...

This paper presents a hybrid unsupervised clustering algorithm, referred to as the Rough Fuzzy C-Means (RFCM) algorithm and Particle Swarm Optimization (PSO). The PSO algorithm features high quality of searching in the nearoptimum. At the same time, in RFCM, the concept of lower and upper approximation can deal with uncertainty, vagueness and indiscernibility in cluster relations while the memb...

From last two decades many optimization techniques have been evolved. PSO and BBO are the two techniques that have been widely used in Swarm Optimization. PSO is better than many genetic algorithms. PSO has applications in various areas like Optimization, Neural Networks training, Fuzzy controls and etc. BBO is based on science of biogeography. BBO has some features common to PSO and Genetic al...

This paper proposes an improved version of particle swarm optimization (PSO) algorithm for the training of a neural network (NN). An architecture for the NN trained by PSO (standard PSO, improved PSO) is also introduced. This architecture has a data preprocessing mechanism which consists of a normalization module and a data-shuffling module. Experimental results showed that the NN trained by im...

Many heuristic-based approaches have been applied to finding schedules that minimize the execution time of computing tasks on parallel processors. Particle Swarm Optimization is currently employed in several optimization and search problems due its ease and ability to find solutions successfully. A variant of PSO, called as Improved PSO has been developed in this paper and is hybridized with th...

Trial and error method can be used to find a suitable design of a fuzzy controller. Generally, the design of fuzzy controller involves determination of the fuzzy rules, Membership Functions (MFs) and scaling factors. An optimization algorithm facilitates the design process and finds an optimal design to achieve a desired performance. This paper presents an Improved Bacterial Foraging Optimizati...