Reinforcement Learning and Multi-Access Edge Computing for 6G-Based Underwater Wireless Networks by Juan Carlos Cepeda-Pacheco, Mari Carmen Domingo

“…These AUVs are strategically positioned to execute tasks either fully locally, partially, or by offloading them entirely to a more resource-equipped AUV (AUV MEC). We achieve this by jointly optimizing the task offloading strategy, resource allocation, and the trajectories of the AUVs. …”
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Electricity pinch analysis method for flexibility supply-demand matching in power systems by Yaling Mao, Tiejiang Yuan, Xueqin Tian, Yue Teng

“…Traditional operation simulation-based planning approaches often fail to provide effective flexibility matching mechanisms, resulting in either insufficient resource allocation or over-provisioning, while struggling to reconcile reliability requirements with computational complexity. …”
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Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments by Ouge Feng, Honghai Zhang, Weibin Tang, Fei Wang, Dikun Feng, Gang Zhong

“…This research provides a theoretical foundation for the scientific management and optimal resource allocation of urban low-altitude airspace, facilitating the safe application and sustainable development of UAVs in urban environments.…”
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Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning by Prashanth Choppara, Bommareddy Lokesh

“…In such simulations, diverse healthcare scenarios, ranging from continuous patient monitoring systems to crucial emergency response applications, are recreated, providing a rich framework for testing the real-time processing capabilities of the model. This algorithm, DRL, has been fine-tuned and extensively implemented in these scenarios to show how the algorithm controls and optimizes tasks and their urgency in accordance with resource demand. …”
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Natural gas bi-level demand response strategies considering incentives and complexities under dynamic pricing by Huibin Zeng, Jie Zhou, Hongbin Dai

“…The upper-level model uses dynamic gas pricing to guide users in adjusting consumption, thereby reducing peaks, filling valleys, and optimizing resource allocation. The lower-level model considers factors like weather and heating, creating incentives to boost user participation and flexibility. …”
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Visual analytics of urban epidemic situation development and dynamic regulation by Song WANG, Shijie CHEN, Hanglin LI, Xiaohui LI, Qiongfang FENG, Huijie WANG

“…In order to solve the reasonable allocation of limited medical resources for patients, a visual platform for dynamic control of cabin hospital was built based on the dataset of the COVID-19 epidemic in Wuhan cabin hospital, which integrates multi-source data such as public opinion, space-time trajectory and science popularization.The droppingwater diagram was introduced to dynamically monitor the overall situation of the cabin hospital.The theme model and sentiment dictionary were used to extract the emotional features of the masses, the WordStream were used to visually present the trend of urban public opinion.The path planning algorithm based on hospital load capacity were built for treatment route, the population-oriented science information of access to cabin hospital and the urban recovery model can enhance anti-epidemic confidence.The system is helpful to realize the reasonable allocation of human and material resources, timely guide the emotional trend of the masses, pay attention to the change of public opinion after the release of new polices/decisions, and slow down the phenomenon of patients gathering.The function and effectiveness of the system was verified by the analysis of several cases.…”
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Kneeliverse: A universal knee-detection library for performance curves by Mário Antunes, Tyler Estro, Pranav Bhandari, Anshul Gandhi, Geoff Kuenning, Yifei Liu, Carl Waldspurger, Avani Wildani, Erez Zadok

“…These points represent optimal trade-offs between cost and performance, facilitating efficient decision-making and resource allocation. However, accurately determining the knees and elbows in curves poses a significant challenge. …”
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A Distributed Low-Degree-of-Freedom Aerial Target Localization Method Based on Hybrid Measurements by Xiaoshuang Jiao, Jinming Chen, Lifeng Jiang, Weiping Li, Xiaochao Yang, Weiwei Wang, Jun Zhang

“…Simulation results validate the significant advantages of the proposed algorithm in enhancing localization accuracy, reducing system costs, and optimizing resource allocation. …”
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A Wind Power Density Forecasting Model Based on RF-DBO-VMD Feature Selection and BiGRU Optimized by the Attention Mechanism by Bixiong Luo, Peng Zuo, Lijun Zhu, Wei Hua

“…Accurate prediction of wind power density (WPD) holds significant practical importance for wind farms, grid operators, and the entire wind power industry, as it facilitates informed decision-making, optimized resource allocation, and enhanced system performance. …”
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Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience by Tzu-Chien Wang, Ruey-Shan Guo, Chialin Chen, Chia-Kai Li

“…To address these limitations, this study proposes a multi-stage data-driven framework integrating latent Dirichlet allocation (LDA) for behavioral insights, deep learning for predictive modeling, and heuristic algorithms for adaptive decision-making. …”
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An interpretable machine learning model to predict hospitalizations by Hagar Elbatanouny, Hissam Tawfik, Tarek Khater, Anatoliy Gorbenko

“…Leveraging a comprehensive dataset sourced from the Mexican government, various supervised learning algorithms including Random Forest, Gradient Boosting, Support Vector Machine, K-Nearest Neighbors, and Multilayer Perceptron are trained and evaluated to discern factors contributing to hospitalizations. …”
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Optimal Operation Method for Microgrid with Wind/PV/Diesel Generator/Battery and Desalination by Qingfeng Tang, Nian Liu, Jianhua Zhang

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Content-based dynamic superframe adaptation for Internet of Medical Things by Yousaf Zia, Arshad Farhad, Faisal Bashir, Kashif Naseer Qureshi, Ghufran Ahmed

“…This article presents a content-based dynamic superframe adaptation algorithm for the low-powered Internet of Medical Things devices to address the resource utilization challenges. …”
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Optimization Method for Network Awareness in Different Domains of LEO Communication Constellation by DI Hang, DONG Tao, LIU Zhihui, WEI Shuotong, ZHANG Qiwei, ZHANG Dingyun

“…The heterogeneous and time-varying characteristics of network resources in LEO communication constellation, as well as the diversities of service requirements, make it difficult to allocate network resources. …”
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Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data by Jember Azanaw, Mihret Melese, Eshetu Abera Worede

“…This study aimed to provide more accurate predictions and data-driven insights that can inform policy-making, resource allocation, and interventions to address Ethiopia’s water crisis. …”
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Fuzzy logic-based particle swarm optimization for integrated energy management system considering battery storage degradation by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, Temitope Ibrahim Amosa

“…The optimal cost for FLB-PSO is $2423.86, representing a cost reduction of $237.23 compared to the $2661.08 of PSO. The FLB-PSO algorithm proficiently manages energy sources while addressing complexities associated with battery storage degradation. …”
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Role,application and challenges of IoT in smart EV charging management:a review by Tripti Kunj, Kirti Pal

“…Additionally, the paper emphasizes the importance of adaptive algorithms and machine learning models for predictive maintenance and efficient resource allocation. …”
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Deep Learning-Driven Geospatial Modeling of Elderly Care Accessibility: Disparities Across the Urban-Rural Continuum in Central China by Yi Yu, Tian Dong

“…Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. …”
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Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth by B. S. Saruk, G. Mokesh Rayalu

“…Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. …”
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Machine learning in predicting firm performance: a systematic review by Yaseen Hezam, Hoa Luong, Lilian Anthonysamy

“…It reveals a predominance of classification methods in ML, with neural networks, logistic regression, and decision trees being the most frequently employed algorithms. These findings underscore the potential of ML techniques to provide a more nuanced and accurate prediction of firm performance by integrating diverse data sources and attributes. …”
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