Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue by Chongde CHEN, Qiang GUO, Ziqiu SONG, Yang HU

“…The wind power offset was decomposed by a Butterworth low-pass filter, and the low-frequency and high-frequency components were used as the reference power of lithium battery energy storage and flywheel energy storage, respectively. In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
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Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data by Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu

“…This framework synergistically integrates an optimized bidirectional hierarchical gated recurrent unit (BiHGRU), a Transformer encoder, and a novel Greenness and Water Content Composite Index, with critical parameters optimized by particle swarm optimization (PSO). …”
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Tuning of Pareto-optimal robust controllers for multivariable systems. Application on helicopter of two-degress-of-freedom by J. Carrillo Ahumada, G. Reynoso Meza, S. García Nieto, J. Sanchis, M.A. García Alvarado

“…The tuning of Pareto-optimal robust controllers was applied to improve the performance of a helicopter with two-degrees-of-freedom with a linear control algorithm. …”
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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. …”
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DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…The predicted values are further optimized via another bioinspired layer that assists in identification of high correlation value changes, thereby improving prediction performance under large data samples. …”
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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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Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…In the case study of a certain urban rail transit line with significant imbalance of passenger flow in different periods, the feasibility and rationality of the above optimized model are verified. ［Result & Conclusion］ The optimized train stock utilization scheme of urban rail transit under the re-coupling operation mode can reasonably optimize the connection between different marshalling train trips and reduce the operation costs for enterprises.…”
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Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S. by Bishwoyog Bhattarai, Zachary Leasor, André Fróes de Borja Reis

“…Corn is one of the most important global agricultural commodities, contributing to food, feed, and fuel production. …”
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Explainable Artificial Intelligence (XAI) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization by Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim, Shuai Zhang

“…We first employed the Tree-based Pipeline Optimization Tool (TPOT), an evolutionary AutoML algorithm, to construct baseline ensemble models using Gradient Boosting (GB), Random Forest (RF), and XGBoost (XGB). …”
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AI-driven generative and reinforcement learning for mechanical optimization of 2D patterned hollow structures by Yicheng Shan, Leitao Cao, Yu Wang, Jing Ren, Chen Huang, Wenli Gao, Shengjie Ling

“…This study demonstrates the efficacy of combining advanced AI techniques for rapid and precise material design optimization, providing a scalable and cost-effective solution for developing superior lightweight materials with tailored mechanical properties for critical engineering applications.…”
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Application of Improved LSTM Model in Runoff Simulation in Arid Region of Northwest China: A Case Study of the Zuli River by SONG Haiping, TANG Yiran, DANG Wentao, WANG Yibo

“…The results indicate that: ① The improved LSTM model demonstrates superior performance in simulating the Zuli River, validating the adaptability of the improved strategies for complex hydrological processes. ② The GWO algorithm significantly enhances the model's prediction accuracy in the basin, confirming the effectiveness of optimization algorithms in parameter calibration. ③The GWO-LSTM-Attention model requires further validation and optimization for future daily-scale simulations and monthly runoff reconstruction.…”
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Optimized Design of Joint Mirror Array and Liquid Crystal-Based RIS-Aided VLC Systems by Omar Maraqa, Telex M. N. Ngatched

“…Due to the non-convexity of the formulated optimization problem, a low-complexity algorithm is utilized to get the global optimal solution. …”
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Optimizing chemotherapeutic targets in non-small cell lung cancer with transfer learning for precision medicine. by Varun Malik, Ruchi Mittal, Deepali Gupta, Sapna Juneja, Khalid Mohiuddin, Swati Kumari

“…For dimensionality reduction, the modified Rime optimization (MRO) algorithm is used to select the best features among multiples. …”
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Machine Learning for Chinese Corporate Fraud Prediction: Segmented Models Based on Optimal Training Windows by Chang Chuan Goh, Yue Yang, Anthony Bellotti, Xiuping Hua

“…We then implement the sliding time window approach to handle population drift, and the optimal training window found demonstrates the existence of population drift in fraud detection and the need to address it for improved model performance. …”
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Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters by Wenmin Wang, Cuijie Diao, Wenqing He, Zhihong Jin, Zaili Yang

“…Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. …”
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Multi-Energy Microgrid Data-Driven Distributionally Robust Optimization Dispatch Considering Uncertainty Correlation by LI Jiawei, SUN Qinghe, WANG Qiong, YE Yujian, HU Heng, ZHANG Xi

“…[Results] Case simulations demonstrate that the proposed distributionally robust model effectively eliminates unrealistic distributions in the ambiguity set，resulting in an 8.16% reduction in out-of-sample costs. The proposed sample-pruning algorithm further reduces the out-of-sample costs by 3.33%. …”
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Optimizing adaptive modulation technique using standard propagation model for enhanced wireless communication channels by Rahim Khan, Zahid Ullah Khan, Sher Taj, Sajid Ullah Khan, Javed Khan, Nazik Alturki, Sultan Alanazi

“…To ensure optimal configuration, an advanced optimization algorithm is employed to dynamically select the most effective SPM parameters, enabling robust performance across varying channel conditions. …”
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Evaluating Sugarcane Yield Estimation in Thailand Using Multi-Temporal Sentinel-2 and Landsat Data Together with Machine-Learning Algorithms by Jaturong Som-ard, Savittri Ratanopad Suwanlee, Dusadee Pinasu, Surasak Keawsomsee, Kemin Kasa, Nattawut Seesanhao, Sarawut Ninsawat, Enrico Borgogno-Mondino, Filippo Sarvia

“…Farmers can apply the maps to gain an overview of the yield variability, improving farm management practices and optimizing inputs to increase productivity and sustainability such as fertilizers. …”
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Distributed robust planning for new power system considering uncertainty and frequency security by Xinxin Zheng, Dahai Zhang, Zhaohong Bie, Xue Wu

“…Secondly, establish a two-stage optimization model for planning and operation under frequency safety constraints, aiming to minimize system costs under frequency safety constraints; Then, iterative solutions are obtained by using column and constraint generation algorithms. …”
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Design and parameter optimization of PBC-NDO composite controller for electric vehicle wireless charging system by YAN Rongge, YAN Chunjiao, YANG Qingxin, ZHANG Xian

“…Aiming at the problems that the charging voltage of the wireless charging system of electric vehicle is unstable due to the offset of the primary and secondary coils and load fluctuation in the process of variable voltage intermittent fast charging, and the controller parameters are mostly selected by empirical value and trial and error method, a composite control strategy combining passivity based controller (PBC) and nonlinear disturbance observer (NDO) based on particle swarm optimization algorithm is proposed. …”
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