This paper proposes the multi-objective variant of recently-introduced fitness dependent optimizer (FDO). The algorithm is called a (MOFDO) and equipped with all five types knowledge (situational, normative, topographical, domain, historical knowledge) as in FDO. MOFDO tested on two standard benchmarks for performance-proof purpose: classical ZDT test functions, which widespread suite that take...

Electroencephalogram signals (EEG) have provided biometric identification systems with great capabilities. Several studies shown that EEG introduces unique and universal features besides specific strength against spoofing attacks. Essentially, is a graphic recording of the brain’s electrical activity calculated by sensors (electrodes) on scalp at different spots, but their best locations...

Poland is facing demanding challenges to achieve a sustainable energy mix in the near future. Crucial and tough decisions must be made about direction of national economy, safety, environmental impact. Considering electricity heating demand forecast, this paper proposes an optimization model based on Grey Wolf Optimizer meta-heuristic support definition ideal considering investment operational ...

Despite Grey Wolf Optimizer's (GWO) superior performance in many areas, stagnation local optima areas may still be a concern. Several significant GWO factors can explored to enhance the of selection classification, with two conflicting concepts considered using or modeling metaheuristic method, exploring search field, and exploiting optimal solutions. Balancing exploration exploitation good man...

The reliability of power packs is very important for the performance of electronic equipment and ensuring the reliability of power electronic circuits is especially vital for equipment security. An alteration in the converter component parameter can lead to the decline of the power supply quality. In order to effectively prevent failure and estimate the remaining useful life (RUL) of superbuck ...

A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The desig...

Abstract In breast cancer image analysis, reliable segmentation of the nuclei is still an open-ended research problem. this paper, a new clustering-based method presented. First, proposed pre-processes histopathology through SLIC method. Then, novel variant multi-objective grey wolf optimizer employed to group obtained super-pixels into optimal clusters. Lastly, cluster with minimum value segme...