Resilience-Improving Based Optimization of Post-Disaster Emergency Maintenance Strategy for Transmission Networks by Haiping LIANG, Haoyan SHI, Yan WANG, Yingpei LIU, Xinming WANG

“…An improved particle swarm optimization (PSO) algorithm is proposed for the optimization model, which uses such methods as the multi-dimensional indefinite length coding, sub-group collaborative optimization, and Monte-Carlo-simulation-based fitness evaluation to improve the standard PSO algorithm. …”
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A Low-Carbon Scheduling Method for Container Intermodal Transport Using an Improved Grey Wolf–Harris Hawks Hybrid Algorithm by Meixian Jiang, Shuying Lv, Yuqiu Zhang, Fan Wu, Zhi Pei, Guanghua Wu

“…The model is solved using an improved grey wolf–Harris hawks hybrid algorithm (IGWOHHO). …”
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The Impact of Different Parallel Strategies on the Performance of Kriging-Based Efficient Global Optimization Algorithms by Hang Fu, Qingyu Wang, Takuji Nakashima, Rahul Bale, Makoto Tsubokura

“…A parallel efficient global optimization (EGO) algorithm with a pseudo expected improvement (PEI) multi-point sampling criterion, proposed in recent years, is developed to adapt the capabilities of modern parallel computing power. …”
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Donor Segmentation Analysis Using the RFM Model and K-Means Clustering to Optimize Fundraising Strategies by Rezki ., Nouval Trezandy Lapatta, Rizka Ardiansyah, Wirdayanti ., Dwi Shinta Angreni

“…This study aims to segment donors using the Recency, Frequency, Monetary (RFM) model and the K-Means algorithm to optimize fundraising strategies. …”
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An innovative coverage optimization method for smart information monitoring in agricultural IoT using the multi-strategy Pelican optimization algorithm by Wei Chen, Qike Cao, Bingyu Cao, Bo Jin

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Research on Cold Chain Logistics Joint Distribution Vehicle Routing Optimization Based on Uncertainty Entropy and Time-Varying Network by Huaixia Shi, Yu Hong, Qinglei Zhang, Jiyun Qin

“…The solution combines simulated annealing strategies with genetic algorithms. It also uses the entropy mechanism to optimize uncertainties, improving global search performance. …”
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Improved gated recurrent unit-based osteosarcoma prediction on histology images: a meta-heuristic-oriented optimization concept by S. Prabakaran, S. Mary Praveena

“…These extracted features undergo the final prediction phase that is accomplished by the novel improved recurrent gated recurrent unit (IGRU), in which the parameter tuning of GRU is accomplished by the osprey optimization algorithm (OOA) with the consideration of error minimization as the major objective function. …”
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Attack resilient IoT security framework using multi head attention based representation learning with improved white shark optimization algorithm by Jawhara Aljabri

“…This paper presents a multi-head attention-driven intrusion detection with improved white shark optimization algorithm (MHAID-IWSOA) methodology in IoT networks. …”
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Research on Day-Ahead Optimal Scheduling of Wind–PV–Thermal–Pumped Storage Based on the Improved Multi-Objective Jellyfish Search Algorithm by Yunfei Hu, Kefei Zhang, Sheng Liu, Zhong Wang

“…The optimization model aims to minimize system operating costs, carbon emissions, and thermal power output fluctuations, while maximizing the regulation flexibility of the VS-PS plant. …”
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Research on electric vehicle charging and discharging optimization scheduling strategy under V2G mode based on improved crisscross algorithm by MA Li, PENG Weilun, FAN Jinheng, ZHOU Zhiming

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Radial Basis Function Neural Network Based on an Improved Exponential Decreasing Inertia Weight-Particle Swarm Optimization Algorithm for AQI Prediction by Jinna Lu, Hongping Hu, Yanping Bai

“…This paper proposed a novel radial basis function (RBF) neural network model optimized by exponential decreasing inertia weight particle swarm optimization (EDIW-PSO). …”
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A low-carbon scheduling method based on improved ant colony algorithm for underground electric transportation vehicles by Yizhe Zhang, Yinan Guo, Yao Huang, Shirong Ge

“…To solve this problem, an improved ant colony optimization algorithm integrated with Q-learning (ACO-QL) is proposed. …”
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Improving the efficiency of frequency regulation for High-Power diesel generators by Shchasiana Arhun, Aleksandr Bogajevskiy, Andrii Hnatov, Nadezhda Kunicina

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Optimizing Rural MG’s Performance: A Scenario-Based Approach Using an Improved Multi-Objective Crow Search Algorithm Considering Uncertainty by Mohammad Hossein Taabodi, Taher Niknam, Seyed Mohammad Sharifhosseini, Habib Asadi Aghajari, Seyyed Mohammad Bornapour, Ehsan Sheybani, Giti Javidi

“…A new optimization method, namely the Improved Multi-Objective Crow Search Algorithm (IMOCSA), is proposed to solve the problem models. …”
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Improved Electrochemical–Mechanical Parameter Estimation Technique for Lithium-Ion Battery Models by Salvatore Scalzo, Davide Clerici, Francesca Pistorio, Aurelio Somà

“…Accurate and predictive models of lithium-ion batteries are essential for optimizing performance, extending lifespan, and ensuring safety. …”
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Fuzzy Fault Tree Maintenance Decision Analysis for Aviation Fuel Pumps Based on Nutcracker Optimization Algorithm–Graph Neural Network Improvement by Weidong He, Xiaojing Yin, Yubo Shao, Dianxin Chen, Jianglong Mi, Yang Jiao

“…Therefore, this paper proposes the NOA (Nutcracker Optimization Algorithm)–GNN (Graph Neural Network) model to enhance the accuracy and robustness of FTA by mitigating the uncertainty and inconsistency in expert knowledge. …”
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An enhanced Walrus Optimizer with opposition-based learning and mutation strategy for data clustering by Laith Abualigah, Saleh Ali Alomari, Mohammad H. Almomani, Raed Abu Zitar, Hazem Migdady, Kashif Saleem, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu

“…The effectiveness of IWO is validated through extensive experiments on multiple benchmark clustering datasets and compared against several state-of-the-art metaheuristic algorithms, including PSO, GWO, AOA, and others. The results demonstrate that IWO achieves better results, indicating improved compactness and separation of clusters. …”
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Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…To achieve high efficiency and high power density designs, it is essential to study core loss characteristics and optimize operating parameters. This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
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CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model by Li Jie, Wang Shuai, Lan Hai, Wang Zhiyong

“…Compared with the traditional BP model, the prediction accuracy is obviously improved, which can meet the needs of practical engineering. …”
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Hidden-layer configurations in reinforcement learning models for stock portfolio optimization by Patrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik Faturohman

“…This study explores the impact of hidden-layer configurations in reinforcement learning models for stock portfolio optimization. Using a portfolio of 45 actively traded stocks in the Indonesian stock market, the performance of four reinforcement learning algorithms—Advantage Actor-Critic (A2C), Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO), and Twin Delayed Deep Deterministic Policy Gradient (TD3)—is evaluated with zero, one, and two hidden layers. …”
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