At present, the restructured electricity market has been a prominent research area and attracted attention. The motivation of restructuring in power system is to introduce competition at various levels generate correct economic signal reduce generation cost. As result, it required have an effective price scheme deliver useful information about power. pricing mechanism dependent on demand load l...

Abstract Strong noise, nonlinearity, and complex frequency are the remarkable symbols of vibration signals when rolling bearing failure. So a new method that improved accuracy fault diagnosis is proposed based on variational mode decomposition (VMD) grey wolf algorithm optimized extreme learning machine (GWO-ELM). The signal decomposed by VMD, Intrinsic Mode Component (IMF) used for fuzzy entro...

<p>One of the greatest techniques, inductive coupling is frequently utilized in biomedical sector for wireless energy transfer to implants. The aim this article develop and analyze effect inductor geometrical characteristics, distance between transmitter (TX) receiver (RX) also operating frequency on power system, using grey wolf optimizer-based cuckoo search (GWO-CS) algorithm. Power eff...

Container-based virtualization has gained significant popularity in recent years because of its simplicity deployment and adaptability terms cloud resource provisioning. Containerization technology is the development computing systems that more efficient, reliable, better overall performance than a traditional virtual machine (VM) based technology. Containerized clouds produce by maximizing hos...

Due to frequent drought events, increased water demand for agricultural production and limited, accurate estimation of reference evapotranspiration (ETo) is necessary developing crop irrigation schemes rational allocation regional resources. The extreme learning machine (ELM) was optimized using four biological heuristic algorithms, namely, Grey Wolf Optimizer (GWO-ELM), Moth-Flame Optimization...

Metaheuristic algorithms are widely used for optimization in both research and the industrial community simplicity, flexibility, robustness. However, multi-modal is a difficult task, even metaheuristic algorithms. Two important issues that need to be handled solving problems (a) categorize multiple local/global optima (b) uphold these till ending. Besides, robust local search ability also prere...

Due to the computational complexity of multilevel image thresholding, Swarm Intelligence Optimization Algorithm (SIOA) has been widely applied improve calculation efficiency. Therefore, more and attention paid exploring application latest SIOA in segmentation. This article takes Otsu fuzzy entropy as objective functions, using Coyote (COA) for thresholds optimization selection, through median a...

Microgrid control in isolated mode is a highly important subject area. In the present paper, a new method is used for controlling the isolated microgrids. This method was used based on the classification of the microgrids into two groups, namely fast-dynamic (battery and flywheel) and slow-dynamic (diesel generator, electrolyzer, fuel cell). For the microgrid components with fast dynamics, a se...

To address the shortcomings of basic Gray Wolf Optimization (GWO) algorithm in solving complex problems, such as relying on initial population, converging too early, and easily falling into local optimality, a chaotic reverse learning initialization strategy, nonlinear control parameter convergence dynamic position update strategy are introduced to develop multi-strategy fusion Improved (IGWO) ...

The vehicle routing problem with time windows and simultaneous pick-ups deliveries (VRPTWSPD) is one of the main distribution planning problems. VRPTWSPD aims to find best plan that minimizes number used total travelled distance. Due NP-Hard nature VRPTWSPD, practical large-scale instances cannot be solved optimality within acceptable computational times. Therefore, it necessary develop approxi...