Absfmct-This paper presents a new approach to economic load dispatch (ELD) problems with non-smwth objective functions using a particle swarm optimization (PSO). In practice, ELD problems have non-smooth objective functions with equality and inequality constraints that make it difficult to find the global optimum using any mathematical approaches. In this paper, a new PSO framework is suggested...

Associative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this paper, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. An FPSO ...

Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. Being a stochastic algorithm, PSO and its randomness present formidable challenge for the theoretical analysis of it, and few of the existing PSO improvements have make an effort to eliminate the random coefficients in the PSO updating formula. This paper analyzes the importance of the randomness in the...

Particle Swarm Optimization (PSO) is a metaheuristic optimization algorithm that owes much of its allure to its simplicity and its high effectiveness in solving sophisticated optimization problems. However, since the performance of the standard PSO is prone to being trapped in local extrema, abundant variants of PSO have been proposed by far. For instance, Fuzzy Adaptive PSO (FAPSO) algorithms ...

In this paper, a facial emotion recognition technique is proposed. The proposed technique employs modified-LBP, which conduct horizontal and vertical neighbourhood pixel comparison, to generate a discriminative initial facial representation. Then, a modified-PSO, is proposed to perform feature optimization.[2] The Facial emotion recognition system consists of three steps: 1) Feature Extraction;...

The problem with development of the support vector machine (SVM) classifiers using modified particle swarm optimization (PSO) algorithm and their ensembles has been considered. Solving this problem would allow fulfilling the highprecision data classification, especially Big Data classification, with the acceptable time expenditures. The modified PSO algorithm conducts a simultaneous search of t...

Many scientific, engineering and economic problems involve optimization. In reaction to that, numerous optimization algorithms have been proposed. Particle Swarm Optimization (PSO) is a new paradigm of Swarm Intelligence which is inspired by concepts from ’Social Psychology’ and ’Artificial Life’. Essentially, PSO proposes that the co-operation of individuals promotes the evolution of the swarm...

The road icing is an adverse weather condition lead to dangerous driving conditions with consequential effects on road transportation. A numerical road icing predication approach is employed for automatic prediction of road icing conditions in three cities of Hubei Province, viz., Wuhan, Shiyan and Xianning. The approach is derived from the support vector machine (SVM). To improve the classific...