Search Results - SHADE algorithm

A novel adaptive L-SHADE algorithm and its application in UAV swarm resource configuration problem by Li, Yintong, Han, Tong, Zhou, Huan, Tang, Shangqin, Zhao, Hui

“…), a novel adaptive L-SHADE algorithm named AL-SHADE is proposed in the study. Two main parts have been modified for L-SHADE…”
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SHADE–WOA: A metaheuristic algorithm for global optimization by Chakraborty, Sanjoy, Sharma, Sushmita, Saha, Apu Kumar, Chakraborty, Sandip

“… This study further enhances the success history-based adaptive differential evolution (SHADE) by hybridizing it with a modified Whale optimization algorithm…”
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Artificial Neural Network Optimal Modeling and Optimization of UAV Measurements for Mobile Communications Using the L-SHADE Algorithm by Goudos, Sotirios K., Tsoulos, George V., Athanasiadou, Georgia, Batistatos, Michael C., Zarbouti, Dimitra, Psannis, Kostas E.

“…) backpropagation algorithm in order to train different ANNs and in particular the L-SHADE algorithm, which self-adapts control parameters and dynamically adjusts population size…”
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Blade optimization design of Savonius hydraulic turbine based on radial basis function surrogate model and L-SHADE algorithm by Ji, Xianglei, Lu, Xuliang, Li, Hongxu, Ma, Penglei, Xu, Shuhui

“…The blade is the component responsible for capturing energy in the Savonius hydraulic turbine, and a good blade shape can extract more energy from the flow…”
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Estimation of ultrasonic flight time based on SHADE algorithm and extended kalman filtering by Mao, Peng, Xiong, Jinglin, Li, Xisheng

“… The algorithm combines an improved Self-Adaptive Differential Evolution (SHADE) algorithm based on successful historical records with an Extended Kalman Filter (EKF…”
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iL-SHADE: Improved L-SHADE algorithm for single objective real-parameter optimization by Brest, Janez, Maucec, Mirjam Sepesy, Boskovic, Borko

“…In this paper we present a differential evolution algorithm (iL-SHADE) for solving single objective real-parameter optimization problems…”
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Inverse Design of Tunable Graphene-Based Terahertz Metasurfaces via Deep Neural Network and SHADE Algorithm by Chen, Siyu, Lin, Junyi, Sun, Jingchun, Li, Xue-Shi

“…) surrogate modeling with success-history-based adaptive differential evolution (SHADE) for tunable graphene-based THz metasurfaces…”
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L-SHADE optimization algorithms with population-wide inertia by Piotrowski, Adam P.

“…) have been considered among the most efficient Evolutionary Algorithms. Various L-SHADE algorithms become the winners of numerous IEEE CEC competitions…”
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L-SHADE-E: Ensemble of two differential evolution algorithms originating from L-SHADE by Wang, Xinxin, Li, Chengjun, Zhu, Jiarui, Meng, Qinxue

“…-SHADE-EpSin, are still not involved in ensemble. Furthermore, ensemble based on similar DE algorithms is rarely reported…”
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Performance improvement of dynamic PV array under partial shade conditions using M 2 algorithm by Manjunath, Matam, Venugopal Reddy, Barry, Lehman, Brad

“…Photovoltaic (PV) plants operating under the partial shade condition show an imbalance in the array irradiance and produce less output power…”
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Thrust distribution of marine power system based on improved SHADE algorithm by ZHU Yuwen, XIAO Jianmei, WANG Xihuai

“… For the traditional SHADE algorithm, an improved SHADE algorithm based on the degree…”
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Design Optimization of Contra-Rotating Axial Flow Fan Using a SHADE-Based Approach by Ait Chikh, Mohamed Abdessamed, Ragueb, Haroun, Ravelet, Florent, Khelladi, Sofiane, Hachemi, Madjid, Belaidi, Idir

“…•Optimization design: The study introduces a novel approach combining the SHADE algorithm and a 1D inverse approach to optimally design a contra-rotating axial fan…”
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Step-by-step improvement of JADE and SHADE-based algorithms: Success or failure? by Piotrowski, Adam P., Napiorkowski, Jaroslaw J.

“…For about two decades Differential Evolution (DE) algorithms belong to the most successful optimization metaheuristics…”
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Novel mutation strategy for enhancing SHADE and LSHADE algorithms for global numerical optimization by Mohamed, Ali W., Hadi, Anas A., Jambi, Kamal M.

“…Proposing new mutation strategies to improve the optimization performance of differential evolution (DE) is an important research study. Therefore, the main…”
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Parameter extraction of solar photovoltaic module by using a novel hybrid marine predators - success history based adaptive differential evolution algorithm by Naraharisetti, Jaya Naga Lakshmi, Devarapalli, Ramesh, Bathina, Venkateswararao

“…) and Success History based Adaptive Differential Evolution (SHADE) algorithm. The principal algorithm for obtaining the optimum solution is MPA…”
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Enhancing SHADE and L-SHADE Algorithms Using Ordered Mutation by Mousavirad, Seyed Jalaleddin, Rahnamayan, Shahryar

“… A Success-History Based Parameter Adaptation for Differential Evolution (SHADE) is a well-established variant of DE algorithm which employs a historical performance of the successful control parameters…”
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An improved adaptive differential evolution optimizer for non-convex Economic Dispatch Problems by Hamdi, Mounira, Idomghar, Lhassane, Chaoui, Mondher, Kachouri, Abdenaceur

“…The present paper proposes an improved adaptive differential evolution algorithm, the IL-SHADE algorithm, to solve Economic Dispatch Problems (EDPs…”
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Minimizing harmonic distortion in power system with optimal design of hybrid active power filter using differential evolution by Biswas, Partha P., Suganthan, P.N., Amaratunga, Gehan A.J.

“…•Non-linear load and source are considered for the system under study.•Application of L-SHADE algorithm is described in detail…”
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A Calibration Algorithm of 3-D Point Cloud Acquisition System Based on KMPE Cost Function by Ren, Lu, Chang, Hao, Liu, Cheng, Chen, Shengmei, Zhao, Lijun, Yang, Tao, Zhang, Wanxu, Wang, Lin

“…For the three-dimensional (3-D) point cloud acquisition system, accurately estimating the measurement model parameters is essential, so a calibration algorithm…”
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Three-Dimensional Path Planning of UAV Based on Improved Particle Swarm Optimization by Deng, Lixia, Chen, Huanyu, Zhang, Xiaoyiqun, Liu, Haiying

“…The traditional particle swarm optimization algorithm is fast and efficient, but it is easy to fall into a local optimum…”
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