Deep reinforcement learning for multi-objective location optimization of onshore wind power stations: a case study of Guangdong Province, China by Yanna Gao, Hong Dong, Liujun Hu, Fanhong Zeng, Yuqun Gao, Zhuonan Huang, Shaohua Wang, Shaohua Wang

“…IntroductionWind energy development faces challenges such as low utilization of wind resources, underdevelopment of suitable areas, and imbalanced electricity demand coverage. …”
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Runoff Prediction and Uncertainty Analysis for Xijiang River Basin Based on CMIP6 Climate Scenarios by WU Huiming, YAN Meng, ZHOU Shuai

“…The results can provide an important scientific basis for water management agencies to plan, allocate, and utilize water resources reasonably in the basin, thereby reducing the influence of GCMs and SSPs uncertainty on runoff prediction uncertainty.…”
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Spatiotemporal Characteristics of Public Attention Level on the 2022 Extreme Drought in Yangtze River Basin Based on Weibo Text Analysis by LI Zhe, CHEN Zhe, XIANG Da-xiang, CUI Chang-lu

“…Utilizing texts from Weibo, a mainstream social media platform in China, as data sources, this study used machine learning and artificial intelligence algorithms to collect Weibo text data throughout the drought progression process. …”
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Smart Electric Vehicle Charging Management Using Reinforcement Learning on FPGA Platforms by Udhaya Mugil Damodarin, Gian Carlo Cardarilli, Luca Di Nunzio, Marco Re, Sergio Spanò

“…The FPGA implementation leverages hardware design strategies to ensure efficient operation and real-time response within a limited amount of required energy, allowing for its implementation in embedded applications and possibly enabling the use of an energy harvesting power source, like a small solar panel. The proposed design effectively manages multiple EV chargers by dynamically allocating current and prioritizing charging tasks to maintain service quality. …”
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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…This system is an efficient tool that properly detects and diagnoses a variety of motor impairment problems using ML algorithms. Decisions are made easier and social health care is improved with the help of this system because timely interventions are implemented, patient outcomes are improved, and resource allocation is optimized.…”
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Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding by Yani Zhang, Qiankun Li, Haijun Duan, Liang Tan, Ying Cao, Junxin Chen

“…Moreover, our research also provides a reference for future preventive control, optimizing medical resource allocation and guiding epidemiological prevention, and guidelines for personal protection against SARS-CoV-2.…”
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A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance by Wenhui Zhang, Fan Gao, Shurui Sun, Qiuying Yu, Jinjun Tang, Bohang Liu

“…This paper focuses on efficiently allocating parking spaces to the demanders. A double-objective model is proposed that considers both the utilizing rate and the walking distance. …”
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Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios by Jie Chen, Kai Xiao, Kai You, Xianguo Qing, Fang Ye, Qian Sun

“…At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. …”
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Secure and fast mobility handover scheme for IoMT in 5 G and future 6 G networks by Shayla Islam, S.M. Topazal, Mohammad Kamrul Hasan, Raenu AL Kolandaisamy, Huda Saleh Abbas, Nguyen Vo, Rahul Thakkar, Muhammad Attique Khan, Deepak Gupta, Dina Abdulaziz AlHammadi

“…The predictive algorithm anticipates device movement and pre-allocates resources at the target Base Station (BS), reducing HO latency by 20–30 % in 5 G and up to 40 % in 6 G. …”
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Joint Configuration and Optimization of Multi-microgrid Shared Energy Storage Based on Coalition Game by Congwei JIANG, Qinghe OU, Zhongchao WU, Jian ZHANG, Shu YANG, Jianan ZHU, Qian AI

“…Firstly, a multi-objective total energy storage configuration model is established, with equipment investment, power fluctuations, and electricity selling and purchase prices considered. Based on the NSGA2 algorithm, the Pareto frontier of the coalition’s overall energy storage planning is obtained. …”
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Prospects of artificial intelligence for the sustainability of sugarcane production in the modern era of climate change: An overview of related global findings by Rajan Bhatt, Akbar Hossain, Debjyoti Majumder, Mandapelli Sharath Chandra, Rajiv Ghimire, Muhammad Faisal Shahzad, Krishan K. Verma, Amarinder Singh Riar, Vishnu D. Rajput, Mauro Wagner Oliveira, Adel Nisi, Riyadh S. Almalki, Viliam Bárek, Marian Brestic, Sagar Maitra

“…Because of the effectiveness, affordability, and efficiency of AI, it is essential in sugarcane agriculture for accurate yield forecasting as well as for streamlining resource allocation and crop management. AI facilitates prompt interventions by assisting in early disease identification and production prediction. …”
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A Time-Efficient Convergecast Scheduling on Star-Linear IWSN for Narrow Process Industries by Hong-hua Xu, Xinping Guan

“…Over the backbone, an optimal slots allocating algorithm is designed to maximize the slots performance in terms of the end-to-end communication reliability, based on which a slot-efficient multisuperframe scheduling algorithm is presented. …”
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AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women by Li Ma, Li Ma, Ru Chen, Weigong Ge, Paul Rogers, Beverly Lyn-Cook, Huixiao Hong, Weida Tong, Ningning Wu, Wen Zou

“…Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. …”
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LAA system dynamic sub-frame configuration strategy in unlicensed bands by Wei JIANG, Shixiao LIU, Heng HU, Chenlu ZHANG

“…The use of dynamic TDD technology in heterogeneous network can effectively increase the system throughput and improve the performance of the system.Due to the limitation of signaling control and other issues,there is usually a dynamic switching between the traditional seven fixed sub-frame ratios in the licensed bands.But as a complement to the LTE system worked in the licensed bands,the unlicensed bands can achieve a more flexible and complete dynamic sub-frame configuration without considering signaling control and other issues.Two new dynamic sub-frame configuration algorithms in unlicensed bands were proposed and compared with traditional static sub-frame configuration,then the impact of dynamic sub-frame allocation algorithms on system performance was verified by LAA system level simulation platform.The results show that the proposed dynamic sub-frame configuration strategies can effectively improve the resource utilization and the overall system throughput.…”
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Load Balancing for Future Internet: An Approach Based on Game Theory by Shaoyi Song, Tingjie Lv, Xia Chen

“…In recent years, countries all over the world consider the future internet as the country’s strategic development directions, so projects about future internet have been launched by these countries. Load balancing algorithms and job allocations are main research problems in areas of resource management of future internet. …”
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Optimal management of the acquiring and evaluating the competencies process of university students by G. A. Dorrer, A. G. Dorrer, G. M. Rudakova

“…The advantage of the methodology, in the opinion of the authors, is that it is possible to easily vary the degree of detail of the accounting of competences – from the total accounting of all competencies, accounting by their types – GC, GP and P, to arbitrary grouping them, up to the allocation of individual or even all competencies. The methodology is based on matrix mathematics, so increasing the dimension of the problem does not cause a change of the calculation algorithms.…”
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Deep Reinforcement Learning-Based Energy Management Strategy for Green Ships Considering Photovoltaic Uncertainty by Yunxiang Zhao, Shuli Wen, Qiang Zhao, Bing Zhang, Yuqing Huang

“…The numerical results demonstrate that, compared to those obtained with the Double DQN algorithm, the PPO algorithm, and the DDPG algorithm without considering the PV system, the proposed DDPG algorithm reduces the total economic cost by 1.36%, 0.96%, and 4.42%, while effectively allocating power between the hydrogen fuel cell and the lithium battery and considering the uncertainty of on-board PV generation. …”
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Classifying Divorce Cases in Iranian Judiciary Courts Using Machine Learning: A Predictive Perspective by Elham Tabrizi, Mohadeseh Farzammehr

“…The findings provide actionable insights for policymakers to develop data-driven strategies for social policy and resource allocation.…”
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Critical Function Placement based on Service Chains in Multi-administrative Federated Networks by Dariusz Nogalski, Dallal Belabed, Alexandre Triollet, Konstanty Junosza-Szaniawski, Slim Abdellatif, Pascal Berthou, Stanislas Pedebearn, Adam Dudko

“…Third, we conduct experiments on various multi-domain topologies and compare the algorithms regarding resource allocation efficiency and runtime. …”
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Efficient Hardware Implementation of a Multi-Layer Gradient-Free Online-Trainable Spiking Neural Network on FPGA by Ali Mehrabi, Yeshwanth Bethi, Andre van Schaik, Andrew Wabnitz, Saeed Afshar

“…By using simple local adaptive selection thresholds, a Winner-Take-All (WTA) constraint on each layer, and a modified weight update rule that is more amenable to hardware, the trainer module allocates neuronal resources optimally at each layer without having to pass high-precision error measurements across layers. …”
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