Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning by Shijin Li, Fucai Wang

“…Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. …”
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Construction Scheduling Optimization of Prefabricated Buildings Under Resource Constraints Based on an Improved Whale Optimization Algorithm by Rui Su, Joey S. Aviles

“…To solve this model effectively, an Improved Whale Optimization Algorithm (IWOA) is developed, addressing the limitations of the standard WOA such as premature convergence and poor local search ability. …”
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A model for assessing lethal resistance levels of various buildings based on improved genetic algorithm + BP neural network optimization by Jie Zhang, Jie Zhang, Bin Tan, Bin Tan, Chaoxu Xia, Wenbin Yan, Yuan Tao, Yuan Tao, Ben Ma, Ben Ma

“…This study proposes a novel model that integrates an improved genetic algorithm (IGA) with an optimized backpropagation neural network (OBPNN) to address data imbalance in classifying building types for lethal resistance levels assessment. …”
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Bus Arrival Time Prediction Based on the Optimized Long Short-Term Memory Neural Network Model With the Improved Whale Algorithm by Bing Zhang, Lingfeng Tang, Dandan Zhou, Kexin Liu, Yunqiang Xue

“…Accurate prediction of bus arrival time is essential to achieve efficient bus dispatch and improve bus trip sharing rate. This article proposes using the improved whale optimization algorithm–long short-term memory (IWOA–LSTM) model to predict bus arrival times and improving the whale algorithm by optimizing the hyperparameters of the LSTM model, so that the advantages and disadvantages of the whale algorithm and the LSTM model can complement each other, thus enhancing the robustness of the model. …”
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A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm by Yong Fan, Guangdong Yang, Yong Pei, Xianze Cui, Bin Tian

“…Traditional empirical formulas often yield unsatisfactory prediction results. To improve the prediction accuracy of the peak particle velocity (PPV), this paper combines the ability of an artificial neural network (ANN) to solve complex nonlinear function approximations and the global optimization ability of 10 metaheuristic optimization algorithms and establishes an improved ANN prediction model. …”
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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

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A Comparative Study on DG Placement Using Marine Predator and Osprey Algorithms to Enhance Loss Reduction Index in the Distribution System by Syazwan Ahmad Sabri, Siti Rafidah Abdul Rahim, Azralmukmin Azmi, Syahrul Ashikin Azmi, Muhamad Hatta Hussain, Ismail Musirin

“…The Marine Predator Algorithm (MPA) and Osprey Optimization Algorithm (OOA) are nature-inspired metaheuristic techniques used for optimizing the location and sizing of distributed generation (DG) in power distribution systems. …”
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Development and Fuel Economy Optimization of Series–Parallel Hybrid Powertrain for Van-Style VW Crafter Vehicle by Ahmed Nabil Farouk Abdelbaky, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. …”
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Optimizing high voltage gain interleaved boost converters for PV and wind systems using hybrid deep learning with bitterling fish and secretary bird algorithms by G.Veera Sankara Reddy, S. Vijayaraj

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Path Optimization Strategy for Unmanned Aerial Vehicles Based on Improved Black Winged Kite Optimization Algorithm by Shuxin Wang, Bingruo Xu, Yejun Zheng, Yinggao Yue, Mengji Xiong

“…The Black-winged Kite Optimization Algorithm (BKA) is likely to experience a sluggish convergence rate when confronted with the optimization of complex multimodal functions. …”
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Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system by Zhe Yin, Zhifan Zhang, Ruijin Zhu, Yifan Zhang, Jiyuan Wang, Wenxing Tang

“…This model combines the entropy weight method (EWM) and non-dominated sorting genetic algorithm II (NSGA-II), improving the objectivity and rationality of uncertainty weight settings in risk-averse strategy (RAS) and risk-seeking strategy (RSS). …”
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Behavior-aware energy management in microgrids using quantum-classical hybrid algorithms under social and demand dynamics by Liu Minghong, Fu Gaoshan, Wang Pengchao, Yuan Xin, Li Qing, Tengfei Hou, Zhang Shuo

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Ballistic Fitting Impact Point Prediction Based on Improved Crayfish Optimization Algorithm by Baolu Yang, Liangming Wang, Jian Fu

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Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…This paper proposes a cooperative sleep and energy-sharing strategy for heterogeneous 5G base station microgrid (BSMG) systems, utilizing deep learning and an improved multi-objective evolutionary algorithm based on decomposition (MOEA/D). …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…A multi-objective optimization model for suspension bridges is presented, which uses layout and dimension parameters as design variables while aiming to reduce cumulative material costs and improve the safety factor, under the premise of meeting design requirements. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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Hub-and-spoke network design to optimize government subsidy costs for maritime transportation in Indonesia by Windra Priatna Humang, Djoko Prijo Utomo, Hasriwan Putra, Dedy Arianto, Rutma Pujiwat, Sucipto, Dwi Phalita Upahita, Nur Fitriana, Maharani Almira Salsabilla, Yustina Niken Raharina Hendra, Asep Yayat Nurhidayat, Mega Novetrishka Putri, Mohamad Ivan Aji Saputro, Amelia Santoso, Ivan Kristianto Singgih, Dina Natalia Prayogo, Indri Hapsari, Olyvia Novawanda, Stefanus Soegiharto, Jerry Agus Arlianto

“…This study introduces a hub-and-spoke model integrated with Milk Run Time Windows (MRTW) to enhance cost efficiency and optimize subsidy expenditures. …”
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Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
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Robotic arm path planning based on the improved dung beetle optimization algorithm by XUAN Yitong, LI Lijun, CHEN Haifei

“…ObjectiveA path planning algorithm based on an improved dung beetle optimization algorithm was proposed to address the challenges in complex scenarios where traditional algorithms for robotic arm path planning often suffer from low efficiency and susceptibility to local optima.MethodsFirstly, the robotic arm and obstacles were modeled using the bounding box method. …”
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A Ultra-Low Cost and Accurate AMC Algorithm and Its Hardware Implementation by Yuqin Zhao, Tiantai Deng, Bill Gavin, Edward A. Ball, Luke Seed

“…In this design, the CAMC algorithm is optimized to fit the FPGA characteristics to further improve the performance, and the computing demands of which could be saved over 94% compared with other state-of-the-art designs. …”
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