Distributed Risk-Averse Optimization Scheduling of Hybrid Energy System with Complementary Renewable Energy Generation by Yanbo Jia, Bingqing Xia, Zhaohui Shi, Wei Chen, Lei Zhang

“…A risk-averse operation optimization model is proposed using conditional value at risk to quantify the uncertainty of renewable energy generation. …”
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Tooth Profile Modification Method of RV Reducer Cycloid Gear Aiming at Optimizing Carrying Capacity by Zongwen An, Panlong Jia, Qiang Wang, Zhili Li, Mingyuan Lei

“…Cycloid gear tooth profile modification is very important to the performance of RV reducer，in order to select the shape modification method and parameter size reasonably and improve the stress state of the cycloid tooth surface，an equidistant & radical-moving modification method based on particle swarm optimization algorithm to optimize bearing capacity is proposed. …”
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Multi-layer Embedded Optimization of Microgrid Capacity Considering Price and Incentive/Compensation Coupling Mechanism by Xianhui ZHU, Xu HU, Nan SHI, Yao ZHANG, Jingwen ZHONG

“…Finally, the optimization models of both the source and load are coupled through the multi-layer embedded mechanism, and a solution model is constructed, which combines the multi-objective particle swarm optimization (MOPSO) algorithm and the particle swarm optimization–imperial competition algorithm (PSO-ICA). …”
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Lithium-Ion Battery State of Health Estimation Based on CNN-LSTM-Attention-FVIM Algorithm and Fusion of Multiple Health Features by Guoju Liu, Zhihui Deng, Yonghong Xu, Lianfeng Lai, Guoqing Gong, Liang Tong, Hongguang Zhang, Yiyang Li, Minghui Gong, Mengxiang Yan, Zheng Ye

“…This paper proposes a novel SOH predication method by combing the four-vector intelligent metaheuristic (FVIM) with the CNN-LSTM-Attention basic model. The model adopts the collaborative architecture of a convolutional neural network and time series module, strengthens the cross-level feature interaction by introducing a multi-level attention mechanism, then uses the FVIM optimization algorithm to optimize the key parameters to realize the overall model architecture. …”
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Fault diagnosis of ZDJ7 railway point machine based on improved DCNN and SVDD classification by Zengshu Shi, Yiman Du, Xinwen Yao

“…Aiming at the unbalanced features of the railway point machine sample, an improved quantity learning algorithm for hypersphere coordinate mapping based on SVDD is proposed. …”
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Multi-strategy enhanced artificial rabbits optimization for prediction of grades in tourism service communication courses by Xiaodan Qu, Zhuyin Jia

“…Results indicate that MEARO outperforms these algorithms. Furthermore, MEARO is used to optimize two critical parameters of the Kernel Extreme Learning Machine (KELM), significantly improving its classification performance. …”
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Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization by Wenli Liu, Yang Chen, Tianxiang Liu, Wen Liu, Jue Li, Yangyang Chen

“…On this basis, a multi-objective intelligent optimization model is established to solve the optimized operating parameters of shield machine by non-dominated sorting genetic algorithm II and technique for order preference by similarity to ideal solution to reduce GS and improve drilling efficiency. …”
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Many-objective optimization scheduling of cascade reservoirs in small watersheds based on an evolutionary multitasking framework by Zheng Wang, Rui Dai, Wanliang Wang, Jing Jie, Qianlin Ye

“…This study develops a many-objective optimization scheduling model for cascade reservoirs in the Lushui River Basin and proposes a constrained many-objective evolutionary multitasking optimization algorithm (EMCMOA) to solve it. …”
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Grey wolf‐based heuristic methods for accurate parameter extraction to optimize the performance of PV modules by Seyit Alperen Celtek, Seda Kul, Manish Kumar Singla, Jyoti Gupta, Murodbek Safaraliev, Hamed Zeinoddini‐Meymand

“…Abstract Parameter prediction for PV solar cells plays a crucial role in controlling and optimizing the performance of PV modules. In this study, the parameter prediction of a four‐diode PV model was carried out using the Improved Grey Wolf Optimization (IGWO) algorithm, which builds upon the Grey Wolf Optimization (GWO) algorithm. …”
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Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization by P. Nirmala, G. Ramkumar, Satyajeet Sahoo, G. Anitha, S. Ramesh, S. Agnes Shifani, Agegnehu Shara Shata

“…PSO-GA (Particle Swarm Optimization and Genetic Algorithm) is utilized to analyze the performance. …”
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Intelligent intrusion detection system based on crowd search optimization for attack classification in network security by Chetan Gupta, Amit Kumar, Neelesh Kumar Jain

“…We have developed the hybrid model based on crow search optimization (CSO) and random forest (RF) algorithm for identifying threats and irregularities in a computer network. …”
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Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton by Yi Long, Zhi-jiang Du, Wei-dong Wang, Wei Dong

“…A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. …”
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Carbon Emission Prediction of Freeway Construction Phase Based on Back Propagation Neural Network Optimization by Lin Wang, Jiyuan Zhu, Haoran Zhu, Wencong Xu, Zihao Zhao, Xingli Jia

“…Furthermore, we integrated multiple strategies to improve the northern goshawk optimization algorithm and optimize the BP neural network, thereby establishing a carbon emission prediction model for the highway construction phase. …”
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Multi-stage Optimization Forecast of Short-term Power Load Based on VMD and PSO-SVR by Wenwu LI, Qiang SHI, Dan LI, Qunyong HU, Yun TANG, Jinchao MEI

“…To reduce the non-linearity of the short-term load sequence and improve the prediction accuracy, a short-term load forecasting model based on multi-stage optimization variational mode decomposition (VMD) and particle swarm optimization optimize support vector regression (PSO-SVR) is proposed. …”
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An adaptive differential evolution algorithm to solve the multi-compartment vehicle routing problem: A case of cold chain transportation problem by Supaporn Sankul, Naratip Supattananon, Raknoi Akararungruangkul, Narong Wichapa

“…The ADE algorithm aims to minimize the total cost, which includes both the expenses for traveling and using the vehicles. …”
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Optimal Skip-Stop Schedule under Mixed Traffic Conditions for Minimizing Travel Time of Passengers by Sun Feng, Zhu Wen-tao, Ye Ying, Wang Dian-hai

“…This paper proposes an optimization model for designing skip-stop service that can minimize the total travel time for passengers. …”
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Multi-Objective Optimization of Offshore Wind Farm Configuration for Energy Storage Based on NSGA-II by Xin Lin, Wenchuan Meng, Ming Yu, Zaimin Yang, Qideng Luo, Zhi Rao, Jingkang Peng, Yingquan Chen

“…How to achieve effective wind power stabilization at the lowest cost has become a key issue. This paper proposes three different energy storage configuration strategies and adopts the non-dominated sorting genetic algorithm (NSGA-II) to conduct multi-objective optimization of the system. …”
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Privacy-preserving detection and classification of diabetic retinopathy using federated learning with FedDEO optimization by Dasari Bhulakshmi, Dharmendra Singh Rajput

“…The FedDEO algorithm optimizes hyperparameters, including learning rates and batch sizes, to enhance model performance. …”
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Intelligent generation and optimization of resources in music teaching reform based on artificial intelligence and deep learning by Ding Cheng, Xiaoyu Qu

“…Therefore, the constructed model can not only generate high-quality personalized melody, but also shows a significant improvement in improving user experience and learning effect, providing reference direction for the generation and optimization of intelligent resources in music teaching.…”
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Optimal Identification for Dynamic PV Cell Parameter Based on a Data-Extension-Driven Method by Yun Long, Youfei Lu, Li Wang, Tao Bao, Chen Chen

“…In order to accurately identify the dynamic parameters of photovoltaics under the general simulation model, traditional parameter identification methods mainly use heuristic intelligent optimization algorithms for direct solution. …”
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