Large Language Model-Assisted Reinforcement Learning for Hybrid Disassembly Line Problem by Xiwang Guo, Chi Jiao, Peng Ji, Jiacun Wang, Shujin Qin, Bin Hu, Liang Qi, Xianming Lang

“…Recycling end-of-life products is essential for reducing environmental impact and promoting resource reuse. In the realm of remanufacturing, researchers are increasingly concentrating on the challenge of the disassembly line balancing problem (DLBP), particularly on how to allocate work tasks effectively to enhance productivity. …”
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OPTIMASI PENJADWALAN PROYEK DENGAN PENYEIMBANGAN BIAYA MENGGUNAKAN KOMBINASI CPM DAN ALGORITMA GENETIKA by Riza Arifudin

“…The allocation of activities is determined based on the earliest start time and latest start time by taking into account the cost of resources in each period of the project. …”
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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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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…Abstract The increasing scale of unconventional oil and gas resource development has driven the demand for complex fracturing technologies. …”
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Optimizing Locations of Primary Schools in Rural Areas of China by Yulong Chen

“…Scientific location selection of schools is an important way to optimize the allocation of educational resources, improve the efficiency of operating schools, and realize the balanced development of education, especially in rural areas. …”
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The moderating role of professional grief in the relationship between job stress dimensions and turnover intention among nurses by Xue Liang, Jue Wang

“…Methods This study utilized linear regression models and the Extreme Gradient Boosting machine (XGBoost) learning algorithm to analyze the impact of the total score of job stress and their dimensions on turnover intention. …”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…Abstract The widespread adoption of cloud services has posed several challenges, primarily revolving around energy and resource efficiency. Integrating cloud and fog resources can help address these challenges by improving fog-cloud computing environments. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…Abstract Background Metastatic spinal disease often leads to significant morbidity, and accurate prediction of postoperative outcomes can help optimize patient management and resource allocation. The development of such a predictive tool is crucial in clinical decision-making and enhancing patient care. …”
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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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Application of 5G + edge computing technology in intelligent monitoring construction of electricity business office by Wei Cui, Junwei Li, Wei Ge, Bo Zhang, Tianwei Liu

“…This paper proposes a heterogeneous node deployment algorithm based on regional density, which divides the network regionally by raster and heterogeneous node communication range, and determines the optimal location of heterogeneous nodes by regional density, realizing the reasonable allocation and utilization of network resources. …”
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Efficient Priority Access to the Shared Commercial Radio with Offloading for Public Safety in LTE Heterogeneous Networks by Chafika Tata, Michel Kadoch

“…The results of the simulation showed that the allocation of radio resources via the courteous mechanism with offloading of new bearers to small cells reduces the rate of blocking bearers and delays the preemption of active bearers present in the LTE HetNets. …”
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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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SUSTAINABLE BACKUP POWER WITH V2G INTEGRATION IN HYBRID MICROGRID by B. Karthikeyan, K. S. Yamuna, K. Padmapriya, S. Priyadharsini, K. Sabareeshwari, P. Sree Mathi

“…The gadget ensures uninterrupted energy for critical systems which includes the Intensive Care Unit and emergency gadget whilst deprioritizing non-vital loads to optimize aid allocation. Advanced manage algorithms dynamically manage power flows ensuring effective operation even in the face of renewable power variability. …”
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Predicting iron contents in the Tamra-Douahria mining site using a deep neural network approach by Zohra Kraiem, Fathi Maalaoui, Salah Bouhlel, Chaouki Sadik, Ali Sdiri

“…Thus, understanding the underlying reasons for this heterogeneity is crucial to optimize the extraction processes, ensuring consistent product quality, and maximizing resource utilization. This was the motivation beyond the attempt allocated to shed light on the behaviour of iron and other related ores in this mining district. …”
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Petrological controls on the engineering properties of carbonate aggregates through a machine learning approach by Javid Hussain, Tehseen Zafar, Xiaodong Fu, Nafees Ali, Jian Chen, Fabrizio Frontalini, Jabir Hussain, Xiao Lina, George Kontakiotis, Olga Koumoutsakou

“…This approach offers significant advantages in the preliminary assessment of aggregate suitability, contributing to more efficient resource allocation in construction projects.…”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. …”
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Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…This method permits for the allocation of multiple log source types through a sliding time window and provides a scalable solution, which is a much-needed function.…”
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Spatial Multi-objective Optimization of Land Use of Kashgar Area Based on NSGA-Ⅱ and GeoSOS-FLUS by Wang Jiaojiao, Yin Xiaojun, Gou Zhenzhen, Liu Shannan, Wang Dimeng

“…[Conclusion] The six land use types were distributed in the landscape in a balanced manner, and the land use type of grassland transition was increased. The optimized land resources can better meet the ecological sustainable development goals, and their layout was more reasonable, providing auxiliary decision-making services for the future allocation of land resources in Kashgar area.…”
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Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration by Junxian Li, Jiaxin Yuan, Xuxin Yue

“…Renewable energy sources include the intermittent nature, which is a vital challenge that causes considerable wind and solar energy losses. …”
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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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