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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Buffer-aided cooperative NOMA with power transfer by Long YANG, Li ZHAO, Yuchen ZHOU, Bingtao HE, Jian CHEN

“…To improve the throughput of multiuser simultaneous wireless information and power transfer systems, a buffer-aided cooperative non-orthogonal multiple access scheme with power transfer was designed to maximize the average throughput under the constraints of average/peak power, user’s rate, and the buffer stability.To reduce the optimization complexity, the Lyapunov’s method was introduced to convert the long-term average optimization problem into a series of time-discrete subproblems, and an adaptive transmission and resource allocation optimization algorithm was proposed, where the working mode, the user scheduling and the power allocation were dynamically optimized according to the time-varying channel/buffer state.Simulation results demonstrate that compared with the existing schemes, the proposed scheme can significantly enhance the average throughput whilst achieving the tradeoff between the delay and throughput.…”
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Semantic aware intelligent optimization for IRS/UAV-enabled MEC in wideband cognitive radio networks by Wei Zheng, Pengshan Ren, Qing Li

“…The proposed semantic-aware optimization framework incorporates semantic information to achieve more efficient task scheduling and resource allocation. Particularly, the proposed optimization framework jointly optimizes UAV trajectories, subcarrier allocation, IRS reflection coefficients, task offloading ratios, task priorities and contextual relevance to maximize semantic utility and system energy efficiency while dynamically ensuring task demands. …”
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Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective by Zheng Shi, Lu Yan, Yingying Hu, Yao Wang, Wenping Qin, Yan Liang, Haibo Zhao, Yongming Jing, Jiaojiao Deng, Zhi Zhang

“…The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. …”
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Federated Synergy: Hierarchical Multi-Agent Learning for Sustainable Edge Computing in IIoT by S. Benila, K. Devi

“…The Industrial Internet of Things (IIoT) presents significant challenges in task offloading, resource allocation, and energy efficiency, necessitating intelligent, scalable, and adaptive solutions. …”
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Energy Efficiency of Full-Duplex Bidirectional Relaying with Asymmetric Traffics by QIAN Chong;JI Xiaodong;TIAN Peisheng

“…The simulation experiments reveal that the proposed algorithm performs well in terms of energy efficiency when the source nodes have asymmetric traffics. …”
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Toward 6G: Latency-Optimized MEC Systems with UAV and RIS Integration by Abdullah Alshahrani

“…This paper addresses the critical challenge of task offloading and resource allocation in an MEC-based system, where a massive MIMO base station, serving multiple macro-cells, hosts the MEC server with support from a UAV-equipped RIS. …”
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Fairness-Aware Computation Offloading for Mobile Edge Computing With Energy Harvesting by Dedi Triyanto, I. Wayan Mustika, Widyawan, Praphan Pavarangkoon

“…Comprehensive simulations demonstrate that the method effectively balances fairness, throughput, and energy use, making it a workable way to improve resource allocation in MEC systems.…”
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Research on Machine Learning-Based Extraction and Classification of Crop Planting Information in Arid Irrigated Areas Using Sentinel-1 and Sentinel-2 Time-Series Data by Lixiran Yu, Hongfei Tao, Qiao Li, Hong Xie, Yan Xu, Aihemaiti Mahemujiang, Youwei Jiang

“…The newly developed framework exhibits exceptional precision in categorization while maintaining impressive adaptability, offering crucial insights for optimizing agricultural operations and sustainable resource allocation in irrigation-dependent arid zones.…”
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Energy- and Spectral-Efficiency Trade-Off in OFDMA-Based Cooperative Cognitive Radio Networks by Xiaomao Chen, Shan Ouyang

“…Optimum transmit power of user is got by analysis; validity of theory is verified by simulation, and the proposed algorithm can adaptively allocate resource for CCRN.…”
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LEO computing satellite constellation design for heterogeneous QoS requirements by PENG Yuming, SUN Yijing, DI Boya

“…A two-stage constellation design algorithm was proposed, which firstly optimized the resource allocation strategy of computational satellites and then determined the constellation parameters under optimal QoS conditions. …”
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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…By leveraging advanced algorithms and machine learning techniques, the research aims to streamline the allocation of tasks and responsibilities among various stakeholders, including farmers, agronomists, technicians, and AI systems. …”
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Optimization of emergency logistics for urban flooding with consideration of rainfall effects by Peiwen Zhang, Chenxing Zhang, Pan Zhang, Xuxian Yan, Huawei Yang

“…Second, a vehicle routing model accounting for rainfall and dynamic vehicle speeds is established, solved using a hybrid Genetic Simulated Annealing algorithm to enhance computational efficiency. Ultimately, through simulation with randomly generated calculation examples, it was found that for the supply distribution model, the allocation model that takes into account both the resource scarcity index and the disaster index is more suitable for scenarios with an uneven distribution of disaster severity. …”
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Mechanism for green unicast routing protection in multi-granularity transport networks by Jun-ling SHI, Xing-wei WANG, Min HUANG

“…The mechanism for green unicast routing protection is designed with the constraint of quality of service (QoS),energy consumption and the survivability of single link or node failure considered.The path is calculated under the constraint of QoS based on K-shortest path algorithm.The resource allocation is done on multi-layer auxiliary graph considering the minimum times of wavelength conversion.Three protection levels are provided according to the service demands.The mechanism is implemented over EON (Europe optical network) topology by simulation.Performance evaluation has been done on the blocking probability,the protecting/working resource ratio and the load balance degree by comparing with certain existent mechanism.It has been shown that the proposed mechanism is both feasible and effective.…”
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Mechanism for green unicast routing protection in multi-granularity transport networks by Jun-ling SHI, Xing-wei WANG, Min HUANG

“…The mechanism for green unicast routing protection is designed with the constraint of quality of service (QoS),energy consumption and the survivability of single link or node failure considered.The path is calculated under the constraint of QoS based on K-shortest path algorithm.The resource allocation is done on multi-layer auxiliary graph considering the minimum times of wavelength conversion.Three protection levels are provided according to the service demands.The mechanism is implemented over EON (Europe optical network) topology by simulation.Performance evaluation has been done on the blocking probability,the protecting/working resource ratio and the load balance degree by comparing with certain existent mechanism.It has been shown that the proposed mechanism is both feasible and effective.…”
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Research on deep reinforcement learning in Internet of vehicles edge computing based on Quasi-Newton method by ZHANG Jianwu, LU Zetao, ZHANG Qianhua, ZHAN Ming

“…To address the issues of ineffective task offloading decisions caused by multitasking and resource constraints in vehicular networks, the Quasi-Newton method deep reinforcement learning dual-phase online offloading (QNRLO) algorithm was proposed. …”
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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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Preventing postoperative pulmonary complications by establishing a machine-learning assisted approach (PEPPERMINT): Study protocol for the creation of a risk prediction model. by Britta Trautwein, Meinrad Beer, Manfred Blobner, Bettina Jungwirth, Simone Maria Kagerbauer, Michael Götz

“…This would ensure optimal patient care and resource allocation and help initiate adequate patient treatment after being transferred from the recovery room to the ward. …”
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Multihop cost awareness task migration with networking load balance technology for vehicular edge computing by Shih-Yang Lin, Jie-Qin Wang, Shi-Ming Peng, Miao-Hui Yang, Shuo Jia

“…This paper investigates dynamic resource allocation and task migration mechanisms for cooperative vehicular edge computing (VEC) servers to expand computing capabilities of local server. …”
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Predicting Intensive Care Unit Admissions in COVID-19 Patients: An AI-Powered Machine Learning Model by A. M. Mutawa

“…Intensive Care Units (ICUs) have been in great demand worldwide since the COVID-19 pandemic, necessitating organized allocation. The spike in critical care patients has overloaded ICUs, which along with prolonged hospitalizations, has increased workload for medical personnel and lead to a significant shortage of resources. …”
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