Bus Arrival Time Prediction Using Wavelet Neural Network Trained by Improved Particle Swarm Optimization by Yuanwen Lai, Said Easa, Dazu Sun, Yian Wei

“…Accurate prediction can help passengers make travel plans and improve travel efficiency. Given the nonlinearity, randomness, and complexity of bus arrival time, this paper proposes the use of a wavelet neural network (WNN) model with an improved particle swarm optimization algorithm (IPSO) that replaces the gradient descent method. …”
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Coordinated optimal scheduling of island microgrid for power-hydrogen-carbon integration based on SAO-NSGA-II algorithm by XI Honglei, SUN Jingliao, QU Hezuo, SHI Zhengchai, HU Changhong, LIU Jinyuan

“…Finally， through simulation examples， a comparative analysis of the results before and after the algorithm improvement is performed， validating the feasibility of the proposed improved algorithm and optimal scheduling model. …”
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A Recommendation Algorithm Based on Restricted Boltzmann Machine by WANG Weibing, ZHANG Lichao, XU Qian

“…In the case where the amount of data is too large, the recommended results output by the RBM model will be broader Besides, many collaborative filtering algorithms currently do not handle large data sets better So, we try to use the deep learning technology to strengthen the personalized recommendation model We propose a hybrid recommendation model combining the bound Boltzmann model and the hidden factor model First, we use the RBM algorithm to generate candidate sets, and score the sparse matrix of the candidate set Then we use the LFM model to sort the candidate results and select the optimal solution for recommendation The hybrid model is validated using used large public datasets It can be seen from the verification that compared with the traditional recommendation model, the proposed method can improve the accuracy of the score prediction…”
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Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer by Chiara Furio, Luciano Lamberti, Catalin I. Pruncu

“…Metaheuristic algorithms (MAs) now are the standard in engineering optimization. …”
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Passivity-Based Control for Rocket Launcher Position Servo System Based on ADRC Optimized by IPSO-BP Algorithm by Rong-lin Wang, Bao-chun Lu, Yuan-long Hou, Qiang Gao

“…Furthermore, to improve the learning capability, the improved PSO algorithm is adopted to optimize the learning rates of the back propagation neural networks. …”
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Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization by Perne Mallikarjun, Sundar Rajan Giri Thulasiraman, Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri

“…The study adopts an Improved Harris Hawk Optimization (IHHO) algorithm to optimize energy management and minimize operational costs under varying scenarios. …”
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Optimizing the neural network and iterated function system parameters for fractal approximation using a modified evolutionary algorithm by Sana Abdulla, K. Mahipal Reddy

“…In this study, we propose an evolutionary optimization strategy to enhance the accuracy and adaptability of RFC splines by optimizing their scaling factor and shape parameters using our novel Fractal Differential Evolution (FDE) algorithm. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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Evaluation and Improvement of Ocean Color Algorithms for Chlorophyll-<i>a</i> and Diffuse Attenuation Coefficients in the Arctic Shelf by Yubin Yao, Tao Li, Qing Xu, Xiaogang Xing, Xingyuan Zhu, Yubao Qiu

“…The proposed OCx-AS series for Chl-<i>a</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub></mrow></semantics></math></inline-formula>-DAS models for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> significantly reduce retrieval errors, achieving RMSE improvements of over 50% relative to global standard algorithms. …”
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Optimal D-STATCOM placement and sizing using a novel bird swarm operated exploitation of elephant herd algorithm by V. Tejaswini, D. Susitra

“…In the 33-bus system at hour 14, the BSOEEH model achieved optimal results, surpassing established methods by significant margins: 1.06% superior to Grey Wolf Optimizer (GWO), 1.02% superior to Whale Optimization Algorithm (WOA), 1.02% superior to the GWO-WOA hybrid model, 0.13% superior to Elephant Herding Optimization (EHO), and 0.93% superior to Backtracking Search Algorithm (BSA). …”
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An integrated stacked convolutional neural network and the levy flight-based grasshopper optimization algorithm for predicting heart disease by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Majad Mansoor, Filippo Sanfilippo

“…This study proposes a novel hybrid model integrating a Stacked Convolutional Neural Network (SCNN) with the Levy Flight-based Grasshopper Optimization Algorithm (LFGOA) to address this challenge. …”
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Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms by Tianyu Li, Xiamin Hu, Tao Li, Jie Liao, Lidan Mei, Huiwen Tian, Jinlong Gu

“…In the initial stage, several classic machine learning models are selected as base models, and the optimal parameters of these models are obtained using the improved metaheuristic-based gray wolf algorithm. …”
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Fast-Charging Optimization Method for Lithium-Ion Battery Packs Based on Deep Deterministic Policy Gradient Algorithm by Zhi Zhang, Taijun Guo, Yefeng Liu, Xinfu Pang, Zedong Zheng

“…The model employs the deep deterministic policy gradient (DDPG) algorithm integrated with reward centralization and entropy regularization mechanisms, aiming to dynamically adjust the charging current to achieve an optimal balance between fast charging and battery health. …”
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A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation by Xi Chen, Yu Wan, Jingtao Qi, Zipeng Zhao, Yirun Ruan, Jun Tang

“…Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). …”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…The novelty of the model stems from the application of the IDBO algorithm, which incorporating Circle chaotic mapping, the Golden sine strategy, and the Levy flight strategy, for hyper-parameter optimization. …”
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Implementing a novel TOPSIS-sine cosine algorithm-based hybrid optimization in machining medium-hardened steel by Ramanuj Kumar, Mohammad Rafighi, Oğur İynen, M. Prem Kumar Reddy, Shrikant Zade, Mustafa Özdemir, Anish Pandey, Ramanpreet Singh

“…This research recommended insert type-3 at optimized cutting conditions to improve machinability and sustainability in turning medium-hard AISI 4340 grade steel.…”
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Identifying influential spreaders based on improving communication transmission model and network structure by Shimeng Zhang, Zejun Sun, Guan Wang, Haifeng Hu, Feifei Wang, Xiaoyan Sun

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An optimized proportional resonant current controller based genetic algorithm for enhancing shunt active power filter performance by Behnam Amini, Hasan Rastegar, Mohammad Pichan

“…Therefore, by performing accurate and optimal adjustments for APF control, system performance and power quality level can be improved significantly. …”
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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

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Revalorization of Vinasse as a Farmland Improver Through Multi-Objective Genetic Algorithms: A Circular Economy Approach by Aarón Montiel-Rosales, Nayeli Montalvo-Romero, Gregorio Fernández-Lambert, Horacio Bautista-Santos, Yair Romero-Romero, Juan Manuel Carrión-Delgado

“…This study showed that vinasse improved soil fertility, quality, and health, with an optimal ratio of mixture formed by 40% vinasse and 60% irrigation water. …”
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