Pulsar identification method based on adaptive grey wolf optimization algorithm in X-ray pulsar-based navigationsHongyang ZhaoJing JinBingjie ShanYu JiangYi Shen
The suggested solution strategy for the OPF issues has been applied to the new IEEE 30-bus electrical network using a hybrid PSO-GWO algorithm, which combines PSO with grey wolf optimization (GWO)25. The hybrid PSO-GWO method performed well in comparison to other algorithms, according to ...
Adaptive Grey Wolf Optimization for Weightage-based Combined Economic Emission Dispatch in Hybrid Renewable Energy SystemsPower systememission costfuel costeconomic dispatchCEEDTo reduce the pollutant atmospheric emission level, a Wind-thermal Economic Emission Dispatch (WTEED) model considering the ...
Reservoir flood control scheduling is a challenging optimization task, particularly due to the complexity of various constraints. This paper proposes an innovative algorithm design approach to address this challenge. Combining the basic walrus optimization algorithm with the adaptive ε-constraint method and...
Zawbaa, H., Emary, E., Hassanien, A.E.: Binary grey wolf optimization approaches for feature selection. Neurocomputing, 371–381 (2016) Abdel-Basset, M., et al.: BSMA: a novel metaheuristic algorithm for multi-dimensional knapsack problems: method and comprehensive analysis. Comput. Ind....
Li L, Sun L, Guo J et al (2017) Modified discrete grey wolf optimizer algorithm for multilevel image thresholding. Comput Intell Neurosci 2017:1–16 Google Scholar Aziz MA, Ewees AA, Hassanien AE et al (2017) Whale Optimization Algorithm and Moth-Flame Optimization for multilevel threshold...
Short-term load forecasting Adaptive grasshopper optimization algorithm Kernel principal component analysis Feature extraction Energy storage system 1. Introduction 1.1. Motivation Smart grid (SG) is an intelligent technology that has gradually gained popularity due to the integration of information and commun...
The Grey Wolf Optimizer (GWO) is a new optimization method applied to diversified objectives in different optimization tasks. Because of its comprehensibility, high flexibility, and quick programmability features [1], and dealing with fewer algorithm parameters, it has attracted significant research inter...
Particle swarm optimization (PSO)8 mimics the behaviour of flocks of birds. Other algorithms in this category include the cuckoo search (CS)9, salp swarm algorithm (SSA)10,11, grey wolf optimization (GWO)12, artificial rabbits optimization13, bat algorithm (BA)14 and naked mole-rat algorithm...
The VBM3D algorithm is an optimization task that equates the denoising problem with the minimization of the cost function. This variational method further improves the performance of VBM3D. Therefore, using traditional methods for processing can also improve the recovery effect of the model. Figure ...