Spatiotemporal pattern analysis of land use in Jiangsu Province based on long-term time series remote sensing images by Zhendong Ji, Lingzhi Yin, Jinhong Wang

“…Studying spatiotemporal patterns of land use is crucial for optimal land resource allocation and sustainable development. This study utilizes the Google Earth Engine (GEE) platform and long-term remote sensing imagery data, selecting Jiangsu Province as a case study area. …”
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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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Study on Optimal Decision of Unit Commitment with Flexible Reserve Participation in Power Grid by ZHOU Yi, LI Yichen, FU Youshu, QIN Kangping, ZHU Wen, FAN Dongqi

“…Secondly, a unit combination model considering the flexible reserve is established with the objective function of minimizing the total operating cost of the system, and the optimization algorithm program is written in the Lingo environment to optimize a variety of reserve resources. …”
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ISCCO: a deep learning feature extraction-based strategy framework for dynamic minimization of supply chain transportation cost losses by Yangyan Li, Tingting Chen

“…By integrating real-time demand data, ISCCO dynamically adjusts the allocation of resources to minimize transportation inefficiencies. …”
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An Efficient Evolutionary Task Scheduling/Binding Framework for Reconfigurable Systems by A. Al-Wattar, S. Areibi, G. Grewal

“…An efficient reconfigurable platform is implemented along with novel placement/scheduling algorithms. The proposed algorithms tend to reuse hardware tasks to reduce reconfiguration overhead, migrate tasks between software and hardware to efficiently utilize resources, and reduce computation time. …”
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Enhancing Triage Systems in Emergency Units: An Extensive Review by Dipankar Maiti, Tincy Mariam Easow, Jyothi R

“… Triage systems in emergency units play a crucial role in prioritizing patient care and optimizing resource allocation during mass casualty incidents or high-demand situations. …”
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Wireless sensor network positioning technology based on improved sampling box and fuzzy reasoning by Ningyun Dan, Lun Zhao, Wenjin Pan, Yan Cai

“…The research results indicate that on the UCI and MIT Reality datasets, the Rand coefficient of the fuzzy clustering algorithm optimized for time series is stable at 0.89 when the weight allocation index is 5, which is superior to other comparative algorithms. …”
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Improving Secrecy Capacity in the Face of Eavesdropping in SWIPT CIoT Networks With Actor-Critic DRL by Nada Abdel Khalek, Walaa Hamouda

“…We then propose a deep reinforcement learning (DRL) approach to determine the optimal strategy for secure transmission and resource allocation. Specifically, we derive the instantaneous secrecy rate and employ a deep deterministic policy gradient (DDPG) algorithm with a lightweight actor-critic architecture to efficiently address dynamic channel occupancy, EH opportunities, and fading conditions. …”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…These improvements contribute to enhanced operational efficiency and better human-machine collaboration by minimizing unnecessary interventions and optimizing resource allocation.…”
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Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models by Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous

“…In particular, accurate regression-based energy forecasting of the energy consumption in various sectors plays a key role in informed decision-making, efficiency improvements, and resource allocation. This paper examines the application of artificial intelligence and supervised machine learning techniques to modeling and predicting the energy consumption patterns in the smart grid sector of a commercial building located in Singapore. …”
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Distributed robust scheduling of distribution-microgrid based on deep learning method integration by WANG Yihong, LIU Jichun, QIU Gao, ZHOU Hao, HE Peixin

“…Considering the uncertainty of the real-time output of new energy in the microgrid, the proposed two-stage robust economic dispatching model adopts column-and-constraint generation (C&CG) and alternating direction multiplier method (ADMM) combines the column and constraint generation algorithm and joint target cascade analysis algorithm for distributed solution. …”
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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…Numerical experiments demonstrate RLEHBA’s superior performance over State-of-the-Art algorithms on the CEC 2017 benchmark. A case study of China’s 2026 pork regulation confirms the system’s practical value in stabilizing the supply-demand balance and optimizing resource allocation. …”
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Multi-Agent Reinforcement Learning-Based Computation Offloading for Unmanned Aerial Vehicle Post-Disaster Rescue by Lixing Wang, Huirong Jiao

“…Second, CER-MADDPG was compared with other baseline algorithms. The results show that compared with MADDPG and stochastic game-based resource allocation with prioritized experience replay, CER-MADDPG achieves the lowest system overhead and superior stability and scalability.…”
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Two-sided Energy Storage Cooperative Scheduling Method for Transmission and Distribution Network Based on Multi-agent Attention-deep Reinforcement Learning by CHEN Shi, ZHU Yujie, LIU Yihong, XU Liuchao, TANG Guodeng

“…To address this, we consider integrating energy storage resources from the transmission grid's power supply side and the distribution grid's user side. …”
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Coalition Game-Based Reinforcement Learning in Underwater Acoustic Networks by Khouloud Gharsalli, Sameh Najeh, Thierry Le Pors, Leila Najjar, Pierre-Jean Bouvet, Hichem Besbes

“…The purpose of this work is to address the limitations of existing resource allocation strategies that rely on static optimization or centralized control, which lack scalability and adaptability in large, dynamic UWA networks. …”
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A Gaussian process approach for contextual bandit-based battery replacement by Zhou Tianshi

“…This research aims to assist electric vehicle providers in optimizing battery replacement schedules, with the objective of minimizing operating losses while meeting evening peak demand. Efficient resource allocation is crucial to remain competitive with the established public transport system. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…By integrating AI into Nigeria’s public health infrastructure, early detection and response can be improved, resource allocation optimized, and disease transmission minimized. …”
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Artificial Intelligence Implementation in Library Information Systems: Current Trends and Future Studies by Albertoes Pramoekti Narendra, Christine Dewi, Lanyta Setyani Gunawan, Ambrosius Sindu Ardi

“…It enables analysis of user behavior and trends, optimizing resource allocation and collection development. By leveraging AI to assess circulation data and usage patterns, librarians can better anticipate user needs and future trends. …”
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Optimization and benefit evaluation model of a cloud computing-based platform for power enterprises by Xueli Yin, Xuguang Zhang, Luyao Pei, Rong Hu, Kaihui Ye, Kangkang Cai

“…The model employs an improved lightweight genetic algorithm combined with an elastic resource allocation strategy to dynamically adapt to task changes across various operational scenarios. …”
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Enhancing Yield Estimation and Field Zoning Accuracy in Precision Agriculture Using Solar-Powered Drone-Based Remote Sensing by Abbas Haider Mohammed, Obaid Mohammed Kadhim, Vittalaiah A.

“…The system processes this data using advanced machine learning algorithms to forecast crop yields and generate detailed field zoning maps, enabling optimized resource allocation and improved farm management. …”
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