An Improved Marriage in Honey-Bee Optimization Algorithm for Minimizing Earliness/Tardiness Penalties in Single-Machine Scheduling with a Restrictive Common Due Date by Pedro Palominos, Mauricio Mazo, Guillermo Fuertes, Miguel Alfaro

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Multi-energy System Planning and Configuration Study for Low-Carbon Parks Based on Comprehensive Optimization Objectives by Yang WANG, Fei LU, Ji LI, Zhukui TAN, Zongyu SUN, Wei XU, Zihong SONG, Zhenpeng LIU

“…Firstly, based on the energy-demand fast prediction method for park and the composite energy system dynamic simulation platform, this paper proposed an optimal planning and configuration method for low-carbon park composite energy system, and established a hybrid optimization algorithm combining Hook-Jeff algorithm and particle swarm optimization. …”
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A traction load modeling method of metro trains based on the regenerative braking energy effective utilization and its application by SHI Dan, GAO Dongsheng, YANG Rui

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Nature-inspired MPPT algorithms for solar PV and fault classification using deep learning techniques by S. Senthilkumar, V. Mohan, S. P. Mangaiyarkarasi, R. Gandhi Raj, K. Kalaivani, N. Kopperundevi, M. Chinnadurai, M. Nuthal Srinivasan, L. Ramachandran

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A novel problem-solving method by multi-computational optimisation of artificial neural network for modelling and prediction of the flow erosion processes by Hossein Moayedi, Atefeh Ahmadi Dehrashid, Binh Nguyen Le

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Model updating method for detect and localize structural damage using generalized flexibility matrix and improved grey wolf optimizer algorithm (I-GWO) by Sina Sadraei, Majid Gholhaki, Omid Rezaifar

“…Furthermore, they show that when compared to grey wolf optimizer (GWO) and particle swarm optimizer (PSO), I-GWO can offer a dependable method for precisely detecting damage.…”
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Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

“…So, this study integrates the ANFIS (adaptive neuro-fuzzy inference system) and ELM (extreme learning machine) machine learning models with three optimization algorithms, i.e., WCA (water cycle algorithm), PSO (particle swarm optimization), and GWO (grey wolf optimizer) to precisely estimate the CS of fiber-reinforced concrete (FRC) containing SiO2. …”
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AquaCrop Plug-in-PSO: A novel irrigation scheduling optimization framework for maize to maximize crop water productivity using in-season weather forecast and crop yield estimation by Mahdi Gholami Sharafkhane, Ali Naghi Ziaei, Seyed Mohammadreza Naghedifar, Amir Akbari, Amir Verdi

“…The main objective of this study was to develop a novel irrigation scheduling optimization framework (AquaCrop plug-in-PSO) for maize, based on in-season weather forecasts integrated with the AquaCrop plug-in model and the particle swarm optimization (PSO) algorithm. …”
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A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression by Tingkai Hou, Zonghong Zhou, Yonggang Zhang, Jing Zhang

“…Secondly, the DE-GWO, particle swarm optimization (PSO), genetic algorithm (GA), and SVR are integrated to identify the optimal superparameters, while the nonlinear mapping relationship between inversion parameters and displacements is established. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

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Research on Parameter Tuning of Electro-Hydrostatic Actuator Position Sliding Mode Controller Based on Enhanced Dynamic Sand Cat Search Optimization Algorithm by Weibo Li, Shuai Cao, Xiaoqing Deng, Junjie Chen, Hao Zhang

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Optimization of Transmission Power in a 3D UAV-Enabled Communication System by Jorge Carvajal-Rodríguez, David Vega-Sánchez, Christian Tipantuña, Luis Felipe Urquiza, Felipe Grijalva, Xavier Hesselbach

“…To this end, using the particle swarm optimization evolution (PSO-E) algorithm, this paper analyzes the impact of user-truncated distribution models for suburban, urban and dense urban environments. …”
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A Two-Stage Optimization Framework for UAV Fleet Sizing and Task Allocation in Emergency Logistics Using the GWO and CBBA by Yongchao Zhang, Wei Xu, Helin Ye, Zhuoyong Shi

“…Subsequently, at the tactical level, the CBBA performs decentralized, real-time task allocation for the optimally sized fleet. We validated our GWO-CBBA framework through extensive simulations against three benchmarks: a standard CBBA with a fixed fleet, a centralized Particle Swarm Optimization (PSO) approach, and a Greedy Heuristic algorithm. …”
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Optimized Support Vector Machine Assisted BOTDA for Temperature Extraction With Accuracy Enhancement by Hongna Zhu, Lei Yu, Yufeng Zhang, Le Cheng, Zhenyu Zhu, Jiayin Song, Jinli Zhang, Bin Luo, Kai Yang

“…Three typical intelligent optimization algorithms, particle swarm optimization algorithm, genetic algorithm and firefly algorithm are explored to optimize the SVM parameters. …”
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Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms by Xiaomin Liao, Yulai Wang, Yang Han, You Li, Chushan Lin, Xuan Zhu

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Taylor-Spotted Cat Optimization (Taylor-SCO): An Energy-Efficient Cluster Head Selection Algorithm with Improved Trust Factor for Data Routing in WSN by Shivaraj Kalburgi, M. Manimozhi

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New Design of Smooth PSO-IPF Navigator With Kinematic Constraints by Mahsa Mohaghegh, Hedieh Jafarpourdavatgar, Samaneh-Alsadat Saeedinia

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Energy Loss Reduction for Distribution Electric Power Systems with Renewable Power Sources, Reactive Power Compensators, and Electric Vehicle Charge Stations by Le Chi Kien, Tran Duc Loi, Minh Phuc Duong, Thang Trung Nguyen

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Multimodal representative answer extraction in community question answering by Ming Li, Yating Ma, Ying Li, Yixue Bai

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Hermetically sealed ecodesign distribution transformer weight optimization considering power losses and total ownership cost (TOC) by Mohammad Hassan Hashemi, Ulas Kilic

“…Specifically, the study employs Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) algorithms to compare their efficacy against conventional design approaches. …”
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