Improved Artificial Bee Colony Optimization Underwater Localization Algorithm by Logistic Chaos Mapping and Differential Evolution by Jiaxing CHEN, Yang LIU, Xiaoqian LIU, Zhihua LIU

“…To address these issues, the improved artificial bee colony optimization underwater localization algorithm by logistic chaos mapping and differential evolution (LDIABC), was proposed. …”
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Solution of optimal power flow with wind power uncertainty using hybridized self-adaptive differential evolution by Harish Pulluri, Tellapati Anuradha Devi, Narsimha Reddy Kuppireddy, Preeti Dahiya, Ch. Naga sai kalyan, B. Srikanth Goud, Mohammad Shorfuzzaman, Ali ELrashidi, Waleed Nureldeen, Ch. Rami Reddy

“…Abstract The current research presents an optimal power flow (OPF) solution in an electrical system network with the integration of wind power using enhanced self-adaptive differential evolution method with a mixed crossover (ESDE-MC). …”
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Multi-Strategy-Assisted Hybrid Crayfish-Inspired Optimization Algorithm for Solving Real-World Problems by Wenzhou Lin, Yinghao He, Gang Hu, Chunqiang Zhang

“…In order to solve problems with the original crayfish optimization algorithm (COA), such as reduced diversity, local optimization, and insufficient convergence accuracy, a multi-strategy optimization algorithm for crayfish based on differential evolution, named the ICOA, is proposed. …”
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Performance evaluation of atmospheric water generation in different climates using thermoelectric cooling by Ali M. Ashour, Sarmad A. Ali, Saif Ali Kadhim, Luttfi A. Al-Haddad, Ali Habeeb Askar, Farhan Lafta Rashid, Ravishankar Sathyamurthy

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Advanced biped gait generator using NARX-MLP neural model optimized by enhanced evolutionary algorithm by Tran Thien Huan, Ho Pham Huy Anh

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Various optimization algorithms for efficient placement and sizing of photovoltaic distributed generations in different networks. by Ahmed A Zaki Diab, Fayza S Mahmoud, Hamdy M Sultan, Abou-Hashema M El-Sayed, Mohamed A Ismeil, Omar Makram Kamel

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Coordinative Optimization of Emergency Control Based on Constraint Consensus and Differential Evolution in Multi-DC Infeed Power Grid by Jun ZHUANG, Deshun WANG, Chenhao GAI, Jinhua XUE, Hongbao ZHU, Changgang LI

“…The vector guides the control scheme to quickly transform into a feasible scheme along the gradient direction of constraint violation. Then, based on the generated feasible control scheme, a differential evolution optimization strategy is designed by using the direction information of the feasible region, so as to explore and develop the feasible region and improve the economy of the scheme. …”
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Optimal Design of Low Sidelobe Sparse Linear Arrays by Li Wang, Fenggan Zhang, Banghuan Hou

“…To optimize the antenna performance in a sparse linear array (SLA) subject to specific constraints of the antenna aperture, number of elements and element spacing, this paper proposes an improved Differential Evolution (DE) algorithm integrating the Cauchy-Gauss mutation strategy. …”
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Performance Evaluation and Optimization of 3D Gaussian Splatting in Indoor Scene Generation and Rendering by Xinjian Fang, Yingdan Zhang, Hao Tan, Chao Liu, Xu Yang

“…Through a systematic quantitative analysis of various performance indicators under differing resolution conditions, threshold settings for the average magnitude of spatial position gradients, and adjustments to the scaling learning rate, the optimal parameter configuration for the 3DGS model, specifically tailored for indoor modeling scenarios, is determined. …”
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An adaptive differential evolution algorithm based on adaptive evolution strategy and diversity enhancement by Shengke Lin, Huarong Xu

“…Differential Evolution (DE) is a widely used and highly effective heuristic global optimization algorithm, but it often stagnates in the later stages of evolution due to a sudden drop in population diversity. …”
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A New Approach to Environmental Economic Dispatch Using Multiobjective Differential Evolution: A Case Study by Carine Nogueira Santino, Jorge Laureano Moya Rodriguez, Cristiano Hora De Oliveira Fontes

“…This new approach was applied together with the Differential Evolution Algorithm in two case studies which comprise a real thermal power plant with ten generating units and an IEEE test system with thirteen generating units. …”
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A Multi-Criteria Perceptual Visual Complexity Metrics-Based Optimization Approach to User Interface Design Layouts by Eren Akca, Omer Ozgur Tanriover, Asim Egemen Yilmaz

“…To this aim, we developed a method that relies on perceptual visual complexity metrics specifically, alignment, balance, density and an introduced measure called distance to focal area. Differential evolution algorithm is adapted to the problem to generate a set of pareto optimal alternative layout designs. …”
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Design of e-commerce product price prediction model based on generative adversarial network with adaptive weight adjustment by Abuduaini Abudureheman, Yan Zhao, Aishanjiang Nilupaer

“…By introducing Wasserstein scatter and removing Lipschitz constraints, we propose the CWGAN model to mitigate data imbalance and enhance the quality of generated samples. Furthermore, we incorporate Adaptive Weight Adjustment (AWA) and a differential evolution strategy, resulting in the Adaptive Weight Adjustment-Conditional Wasserstein Generative Adversarial Network (AWA-CWGAN) algorithm. …”
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An Innovative Hybrid Approach Producing Trial Solutions for Global Optimization by Vasileios Charilogis, Glykeria Kyrou, Ioannis G. Tsoulos, Anna Maria Gianni

“…Then, the generated solutions are used to form new test solutions, by applying differential evolution techniques. …”
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A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution by Fangping Xu, Hui Yang, Jianyong Zhu, Wenjia Chang

“…Taking into account the multi-modal and multi-variable characteristics of the optimized objective function, we put forth an enhanced version of the improved differential evolution algorithm, the Linear-Chaos and Two Mutation Strategies of Adaptive Differential Evolution (LCTADE)with Covariance Matrix and Cauchy Perturbation(CC-LCTADE). …”
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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…In addition, there is also scope for further improvement through the application of still under-utilized optimization techniques. Thus, the present article proposes a novel approach that leverages the Differential Evolution (DE) algorithm to optimize hyperparameters within three selected ML models, with the aim of classifying singing-voice registers i.e., chest, mixed, and head registers). …”
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An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

“…Second, a new differential evolution mutation strategy with a periodic retrospective adaptive mutation factor was proposed. …”
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Advanced Deep Learning Methods to Generate and Discriminate Fake Images of Egyptian Monuments by Daniyah Alaswad, Mohamed A. Zohdy

“…An improved discriminator design that combined noise addition with squeeze-and-excitation blocks and a modified MinibatchStdLayer produced 27.5% better Fréchet Inception Distance performance than the original discriminator models. Moreover, differential evolution for latent-space optimization reduced alignment mistakes during specific monument construction tasks by about 15%. …”
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Physics-Informed Neural Networks: A Review of Methodological Evolution, Theoretical Foundations, and Interdisciplinary Frontiers Toward Next-Generation Scientific Computing by Zhiyuan Ren, Shijie Zhou, Dong Liu, Qihe Liu

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Predicting the Evolution of the Supercontinuum Generation With CNN-LSTM Model by Yi Feng, Ruiyuan Liu, Xinyue Chang, Xiangzhen Huang, Yuan He, Ning Li, Tiantian Zhou, Chujun Zhao

“…The combined neural network can effectively solve the complex nonlinear propagation problems and maintain high accuracy compared with the LSTM, GRU neural networks for different incident power. The hybrid approach can facilitate the design and optimization of the spectral or temporal intensity distribution of SC generation, and may offer guidance for designing SC source for specific applications.…”
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