Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…The precise prediction of wind power is essential not only for the smooth integration into the power grid but also for the optimization of unit commitment, maintenance scheduling, and the improvement of power traders' profitability. …”
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Control Strategy for PHEB Based on Actual Driving Cycle with Driving Style Characteristic by Jianping Gao, Zhenhai Xu, Xiaojie Gao

“…Based on the 6 driving cycles, the key parameters of rule-based control strategy are optimized and established by a combinatorial optimization algorithm in Isight. …”
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Phase diagram from nonlinear interaction between superconducting order and density: toward data-based holographic superconductor by Sejin Kim, Kyung Kiu Kim, Yunseok Seo

“…We introduce positional embedding layers to improve the learning process in our algorithm, and the Adam optimization is used to predict the critical temperature data via holographic calculation with appropriate accuracy. …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Experimental results demonstrate that RIM-Net achieves an average accuracy of 92.36% on benchmark datasets while maintaining generalization capabilities above 85% in unseen environments. Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…This study investigates the application effectiveness of deep learning-based object detection technology in forest fire smoke recognition by using the YOLOv11x algorithm to develop an efficient fire detection model. …”
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Research Status and Development Trends of Deep Reinforcement Learning in the Intelligent Transformation of Agricultural Machinery by Jiamuyang Zhao, Shuxiang Fan, Baohua Zhang, Aichen Wang, Liyuan Zhang, Qingzhen Zhu

“…This paper proposes research directions from three key dimensions-“algorithm capability enhancement, deployment architecture optimization, and generalization ability improvement”-offering theoretical references and practical pathways for the continuous evolution of intelligent agricultural equipment.…”
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Reliability Prediction for Computer Numerical Control Machine Servo Systems Based on an IPSO-Based RBF Neural Network by Zheng Jiang, GuangJian Wang, ZuGuang Huang, Ye He, RuiJuan Xue

“…A novel reliability prediction model based on radial basis function (RBF) neural network optimized by improved particle swarm optimization (IPSO) was proposed. …”
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Industrial-Grade 3D Detection for Laser Cleaning of Metallic Components Based on Neural Radiance Fields and Temporal-Spatial Learning by Dandan Qi

“…Improve the collaborative modeling ability between multi-temporal images through cross-scale attention fusion; 4. …”
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Research on the evaluation method of cooperative jamming effectiveness based on IPSO-ELM by A. Tianjian Yang, B. Xing Wang, C. Siyi Cheng, D. You Chen, E. Xi Zhang

“…This optimization aims to boost the model’s predictive precision. …”
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Investigating employment patterns and determinants in the European Union through panel data insights by Vasilescu Maria Denisa, Stănilă Larisa, Crivoi Silvana, Belu Maria Berta

“…The clustering algorithm identified the heterogeneity of the countries, indicating an optimal number of three clusters for the grouping of EU states, considering the set of variables used. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…Through rigorous analysis, the properties with the most significant influence on solubility were identified and subsequently used as input features for four ensemble machine learning algorithms: Random Forest, Extra Trees, XGBoost, and Gradient Boosting. …”
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Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets by Mojtaba Fereydani, Mohammad Amin Latify

“…A column & constraint generation (C&CG) algorithm is used to solve the model. Numerical results demonstrate the model’s effectiveness in various case studies, showing that the GenCo can manage wind uncertainties, benefit from arbitrage opportunities in electricity and gas markets, and improve economic outcomes. …”
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Research on False Alarm Rate Reducing Strategies for Subway Train Fire Alarm System by ZHANG Qian, XU Shaohong, XUE Hongquan

“…The false alarm rate can be reduced by hardware optimization methods such as adding dust filter devices, adopting dual light source detectors, multi-parameter gas detectors and pyrolysis particle detectors; the rate can also be reduced by optimizing software algorithms (optimization modeling method, automatic adjustment of alarm thresholds, machine self-learning algorithm, etc.). …”
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基于modeFRONTIER的离合器碟形弹簧多目标优化设计 by 潘金坤

“…Based on the analysis of the working characters of disc springs in clutch,the mathematical model of multi-objective optimal design of disc springs is established with unified objective function method,which regards the minimization of the disc spring volume and its average variable quantity of working compress force within the scope of friction lining wear as optimal objectives.The optimization calculation is presented by using the software modeFRONTIER.The results indicate that the relevant performance of disc springs is significantly improved after optimal design,with the objective function values reduced by 36% and 6% respectively.The software modeFRONTIER,with its simplicity and efficient algorithm,solves optimization problems and improves design efficiency.…”
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Research on planning and demand matching strategies for intelligent material supply chains under carbon constraints by Shao Xuwei, Wu Jianfeng, Ge Junping, Wang Jianguo, Hu Kairui, Qiu Yang, Ju Chunhua, Xu Jiaming

“…Therefore, starting from the matching fitness of both supply and demand sides, this paper constructs a dynamic matching decision framework that is more in line with the actual operation logic, and introduces a dynamic matching algorithm based on multi-factor stimulus value and response threshold to improve the adaptability and responsiveness of the model. …”
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Bearing Fault Diagnosis in the Mixed Domain Based on Crossover-Mutation Chaotic Particle Swarm by Tongle Xu, Junqing Ji, Xiaojia Kong, Fanghao Zou, Wilson Wang

“…Finally, the support vector machine is optimized using the improved chaotic particle swarm to improve fault classification diagnosis. …”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…In this paper, we present an approach that transcends merely eliminating domain discrepancies by enhancing the model's adaptability to improve its performance in unseen domains. …”
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Balancing resource utilization and slice dissatisfaction through dynamic soft slicing for 6G wireless networks by Zeinab Sasan, Siavash Khorsandi

“…Given the NP-hard nature of the problem, we propose the Heuristic Resource Allocation for Soft Slicing (HRASS) algorithm, which achieves near-optimal performance with significantly reduced computational complexity. …”
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Downscaling of ERA5 reanalysis land surface temperature based on attention mechanism and Google Earth Engine by Shiyu Li, Hong Wan, Qun Yu, Xinyuan Wang

“…In addition, the Bayesian global optimization algorithm is used to select the optimal hyperparameters of the network in order to enhance the predictive performance of the model. …”
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