نتایج جستجو برای: augmented grey wolf optimization algorithm

تعداد نتایج: 1033761  

Journal: :Journal of Electrical Engineering & Technology 2020

2016
Lu WANG Ya-Ping MA Qi-Jun ZHOU Ya-Ping ZHANG Peter SAVOLAINEN Guo-Dong WANG

The grey wolf (Canis lupus) is one of the most widely distributed terrestrial mammals, and its distribution and ecology in Europe and North America are largely well described. However, the distribution of grey wolf in southern China is still highly controversial. Several well-known western literatures stated that there are no grey wolves in southern China, while the presence of grey wolf across...

2015
Ahmed A. M. El-Gaafary Yahia S. Mohamed Ashraf Mohamed Hemeida Al-Attar A. Mohamed

Grey wolf optimizer (GWO) is a new technique, which can be applied successfully for solving optimized problems. The GWO indeed simulates the leadership hierarchy and hunting mechanism of grey wolves. There are four types of grey wolves which are alpha, beta, delta and omega. Those four types can be used for simulating the leadership hierarchy. In order to complete the process of GWO a three mai...

Journal: :Advances in Space Research 2022

Fast and accurate identification of pulsar signals is important for X-ray pulsar-based navigation (XNAV). Traditional signal detection technology based on FFT search epoch folding (EF) requires a very long time to obtain an appropriate signal-to-noise ratio (SNR) gain, especially weak with low photon fluxes. This paper proposes adaptive stochastic resonance (SR) method the grey wolf optimizer (...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه بوعلی سینا - دانشکده علوم پایه 1391

abstract: in this thesis, we focus to class of convex optimization problem whose objective function is given as a linear function and a convex function of a linear transformation of the decision variables and whose feasible region is a polytope. we show that there exists an optimal solution to this class of problems on a face of the constraint polytope of feasible region. based on this, we dev...

Journal: :Journal of physics 2023

Abstract In view of the time-series characteristics grid load data, this paper proposes a method to predict electricity demand by optimizing long-and short-term memory (LSTM) neural network model using grey wolf optimization algorithm, taking into account effects time, weather conditions and holiday on loads. The overcomes disadvantage that backpropagation through time algorithm tends converge ...

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