A Multistep Iterative Ranking Learning Method for Optimal Project Portfolio Planning of Smart Grid by Cong Liu, Xianghua Li, Jian Liang, Kun Sheng, Lingzhao Kong, Xiaoyan Peng, Wenxin Zhao

“…The optimal project portfolio planning problem of power grid is formulated as the optimization process of massive project priority sorting with an improved knapsack model. …”
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Energy Interaction and Energy Storage Sharing Optimization Method for Users, Base Stations, and Charging Stations by HU Long, FANG Baling, FAN Feilong, CHEN Dawei, LI Xinxi, ZENG Run

“…Next, incorporating 0-1 integer variables, a solution method utilizes the adaptive differential evolution algorithm combined with the mixed-integer optimization theory. …”
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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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A cluster-optimized regulation method for distribution networks considering distributed photovoltaic heterogeneous characteristics by Junhao Li, Xin Wang, Qi Guo, Chunzhi Yang, Yizhe Chen, Ruifeng Zhao, Ming Li

“…Further, a DN cluster-optimized model considering the DPV heterogeneous characteristics is constructed to achieve multi-objective optimization of the integrated DN operation cost and node voltage deviation. …”
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Co-Optimization of Market and Grid Stability in High-Penetration Renewable Distribution Systems with Multi-Agent by Dongli Jia, Zhaoying Ren, Keyan Liu

“…The methodological innovations primarily include an enhanced scheduling algorithm for coordinated optimization of renewable energy and energy storage, and a dynamic coordinated optimization method for EV clusters. …”
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Optimal Scheduling of Biomass-Hybrid Microgrids with Energy Storage: An LSTM-PMOEVO Framework for Uncertain Environments by Zichong Wang, Yingying Zheng

“…Finally, a public dataset was utilized for the experiments to verify the performance of the proposed algorithm. Comparisons and discussions show that the proposed optimization strategies significantly improve the performance of PMOEVO, demonstrating marked advantages over six classical algorithms. …”
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Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data by Zhihong Li, Han Xu, Shiyao Qiu, Jun Liu, Kairan Yang, Jiahao Wu

“…To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. …”
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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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Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core by Kyeong-Tae Yu, Hwi-Rang Ban, Seong-Won Kim, Jun-Beom Park, Jang-Young Choi, Kyung-Hun Shin

“…The optimized WFSM achieved a 13.97% increase in power density and a 1.0% improvement in efficiency compared to the baseline NOES model. …”
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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

“…The MTSP ( multiple traveling salesman problem) is introduced to construct an optimized train stock utilization model during the transition period from peak to off-peak passenger flow in urban rail transit. …”
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A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading by Asma Sattar, Amna Sarwar, Saira Gillani, Maryam Bukhari, Seungmin Rho, Muhammad Faseeh

“…This study proposed an improved stock market trading framework termed the RMS-Driven Deep Reinforcement Learning (DRL) model for optimal portfolio management. …”
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An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning by L. Ravi Kumar, Ravi Kumar Tata, T. R. Mahesh, Endris Mohammed Ali

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

“…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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Synergistic hyperspectral and SAR imagery retrieval of mangrove leaf area index using adaptive ensemble learning and deep learning algorithms by Jun Sun, Weiguo Jiang, Bolin Fu, Hang Yao, Huajian Li

“…We confirmed that 1D-CNN + DNNR provided an effective approach to estimating the mangrove LAI, as it produced a higher-accuracy inversion (R2 = 0.8685) than that of the AELR model. It was found in this study that the 1D-CNN improved the retrieval accuracy (R2) of the mangrove LAI from 0.097 to 0.1297 when compared with the traditional data dimension reduction (DDR) method, which demonstrated that the 1D-CNN was able to improve the inversion accuracy of the mangrove LAI. …”
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A GIS-based integrative approach for land use optimization in a semi-arid watershed by S.M. Tajbakhsh, H. Memarian, A. Kheyrkhah

“…In line with the management of natural resources, land use optimization can be highly useful. The aim of the present study is to propose an appropriate integrative model for optimized allocation of lands for surface runoff and sediment load minimization and net income maximization in Bayg watershed, Iran. …”
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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…The proposed model trained with all weeks’ data demonstrated superior performance, showing significant improvements in F1-scores and recall, particularly for the minority class of at-risk students. …”
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Numerical simulation of optimal jet angle of water jet assisted disc cutter rock breaking by Anxin WANG, Yiqiang LU, Sheng ZHANG, Jianhong MA, Zhanbiao YANG, Hongyun FAN

“…Aiming at the reasonable determination of the optimal rock breaking impact angle of water jet assisted hob, a discrete element model of equivalent crystalline rock material based on Thiessen polygon algorithm was built. …”
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Optimizing Scheduled Virtual Machine Requests Placement in Cloud Environments: A Tabu Search Approach by Mohamed Koubàa, Abdullah S. Karar, Faouzi Bahloul

“…Our algorithm demonstrates significant improvements over existing placement methods, achieving up to a 15% increase in resource efficiency compared to baseline approaches. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…A multi-objective optimization model is also established, further illustrating the algorithm’s performance and its effectiveness in balancing the number of sensors and coverage rate. …”
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Hate Speech Detection and Online Public Opinion Regulation Using Support Vector Machine Algorithm: Application and Impact on Social Media by Siyuan Li, Zhi Li

“…By maximizing the category interval to locate the optimal hyperplane and combining nuclear techniques to implicitly adjust the data distribution, the classification accuracy of hate speech detection is significantly improved. …”
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