Flash-Attention-Enhanced Multi-Agent Deep Deterministic Policy Gradient for Mobile Edge Computing in Digital Twin-Powered Internet of Things by Yuzhe Gao, Xiaoming Yuan, Songyu Wang, Lixin Chen, Zheng Zhang, Tianran Wang

“…Offloading decisions and resource allocation problems in mobile edge computing (MEC) emerge as key challenges as they directly impact system performance and user experience in dynamic and resource-constrained Internet of Things (IoT) environments. …”
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Interference Mitigation in Coexisting Satellites and Cloud-Assisted Ground Networks in the mmWave Band by Sirine Ben Ati, Hayssam Dahrouj, Mohamed-Slim Alouini

“…Such coexistence of space and ground communications becomes prone to wireless interference, and so the cross-development of intelligent resource allocation techniques becomes indispensable for assessing the benefit of such hybrid space-ground networks. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…This research offers valuable insights into the implementation of EV sharing systems in educational institutions, emphasizing the advantages of focused resource allocation and the integration of dynamic decision variables.…”
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Synergizing NOMA and energy harvesting in full duplex mobile edge computing for optimized energy efficiency by Mirza Baber Baig, Taoshen Li, Muhammad Zain Yousaf, Mohit Bajaj, Arvind R. Singh, Milkias Berhanu Tuka

“…Full-duplex base stations simultaneously manage task offloading and energy transmission, improving resource utilization. A Block Coordinate Descent (BCD)-based algorithm addresses the non-convex optimization challenge, offering an optimal solution. …”
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Multi-Modal Federated Learning Over Cell-Free Massive MIMO Systems for Activity Recognition by Seyed Mohammad Sheikholeslami, Pai Chet Ng, Jamshid Abouei, Konstantinos N. Plataniotis

“…Additionally, we employ a modified Particle Swarm Optimization (PSO) algorithm for efficient resource allocation. Extensive experiments validate our framework, demonstrating substantial reductions in training time and significant improvements in model performance, particularly an average improvement of 15% and 23% in test accuracy compared to the other fusion models when missing one and two modalities in the inference phase.…”
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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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Processing streams in a monitoring cloud cluster by Alexey N. Nazarov

“…The International Telecommunication Union’ (ITU) recommendations Y. 3510 present the requirements for cloud infrastructure that require monitoring the performance of deployed applications based on the collection of real-world statistics. Often, computing resources of monitoring clusters of cloud data centers are allocated for continuous parallel processing of high-speed streaming data, which imposes new requirements to monitoring technologies, necessitating the creation and research of new models of parallel computing. …”
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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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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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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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