Analysis of disease severity and mortality prediction using machine learning during COVID-19 by Hodjat (Hojatollah) Hamidi, Mostafa Moradi

“…This study helps healthcare centers and hospitals prioritize the allocation of medical resources based on the severity of patients' conditions and predict their chances of survival. …”
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Predicting patient risk of leaving without being seen using machine learning: a retrospective study in a single overcrowded emergency department by Arianna Scala, Teresa Angela Trunfio, Massimo Majolo, Michelangelo Chiacchio, Giuseppe Russo, Paolo Montuori, Giovanni Improta

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A Hybrid Approach to Traffic Incident Management: Machine Learning-Based Prediction and Patrol Optimization by Yusuf Sait Turkan, Mesut Ulu

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Automatic Scheduling Method for Customs Inspection Vehicle Relocation Based on Automotive Electronic Identification and Biometric Recognition by Shengpei Zhou, Nanfeng Zhang, Qin Duan, Jinchao Xiao, Jingfeng Yang

“…Traditional vehicle scheduling often relies on manual processes and simplistic algorithms, resulting in prolonged waiting times and inefficient resource allocation. …”
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Multi-objective optimal probabilistic planning in distribution systems considering load growth by Ayat Saleh

“…This paper presents the operation of distribution networks with dispatch able mix of different types of distributed energy resources (DERs) units considering load growth up to planning period based on Multi Variant Differential Evolution algorithm (MVDE). …”
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Hybrid Models for Forecasting Allocative Localization Error in Wireless Sensor Networks by Guo Li, Hongyu Sheng

“…This study presents a machine learning-based approach to forecast Allocative Localization Error (ALE) in Wireless Sensor Networks (WSNs), addressing challenges such as dynamic network topologies and resource constraints. …”
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A node deployment and resource optimization method for CPDS based on cloud‐fog‐edge collaboration by Xiaoping Xiong, Geng Yang

“…Subsequently, an improved multi‐objective particle swarm optimization algorithm (MWM‐MOPSO) is employed to solve the task resource allocation problem. …”
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Multiple UAV Swarms Collaborative Firefighting Strategy Considering Forest Fire Spread and Resource Constraints by Pei Zhu, Rui Song, Jiangao Zhang, Ziheng Xu, Yaqi Gou, Zhi Sun, Quan Shao

“…To address the demands of efficient forest fire detection and suppression, an adaptive multiple UAV swarm collaborative firefighting strategy considering dynamic forest fire spread and resource constraints was proposed in this paper. The multiple UAV swarm adaptive information-driven collaborative search (MUSAIDCS) algorithm and the resource-limited firefighting model were established. …”
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Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

“…This provides a scientific basis for enterprises to allocate human resources reasonably and improve project efficiency. …”
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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…Cloud resource brokerage is a fundamental challenge in cloud computing, requiring the efficient selection and allocation of services from multiple providers to optimize performance, sustainability, and cost-effectiveness. …”
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Intelligent Integration Method of AI English Teaching Resource Information under Multi-Agent Collaboration by Minjuan Liu

“…Moreover, this article analyzes the principles and properties of the three algorithms, ALO, GWO, and MFO, and integrates them into the D2D power allocation problem in the two communication modes. …”
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Application-oriented resource matching model based on trust for internet-based virtual computing environment by Chun-ge ZHU, Xin-ran LIU, Yi-xian YANG, Hong ZHANG

“…In order to solve the problem of reasonable resource s ing in the virtual computing environment (iVCE),a resource matching model,based on trust “resource sliding window” model,was proposed.Firstly,the resources were classified in advance by their static properties.Then the resource nodes were evaluated by a trust model based on the time window and Bayesian algorithm,and the evaluated results as well as the resource load were fused to determine the levels of the dynamic real-time performance.Finally,the scheduling resources were allocated according to the comprehensive assessment of the static and dynamic properties of the resource nodes.The proposed model provides a basis of scheduling strategy for different resources with different tasks and attributes,thus achieving the goal of “proper resources’ serving proper tasks”.Simulation results show that,compared the previous scheduling algorithm,the proposed model has better performance in the success rate of task execution and the rate of resource utilization.…”
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Research on low-energy-consumption deployment of emergency UAV network for integrated communication-navigating-sensing by Li WANG, Qing WEI, Lianming XU, Yuan SHEN, Ping ZHANG, Aiguo FEI

“…In public emergencies such as accident relief, rescue workers are faced with challenges, such as poor communication, unstable navigating, and inaccurate disaster sensing.It is necessary to deploy an emergency unmanned aerial vehicle (UAV) network to guarantee the services of communication-navigating-sensing.Aiming at alleviating the problem of limited energy of UAV, a low-energy-consumption deployment of an emergency UAV network was first proposed for integrated communication-navigating-sensing (ICNS).The proposed scheme was able to realize network topology reconstruction and role cognition on demand.Then, a particle swarm algorithm based hierarchical matching decision-making algorithm was presented to jointly optimize three sub-problems, including the associations between UAVs and users, the resource allocation for multi-role UAV communications, and the UAV position.Simulation results show that the proposed ICNS scheme can achieve flexible adaptation of the multi-objective requirements and limited network resources, and dramatically reduce the demand for the number of UAVs and the deployment energy consumption.…”
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Research on low-energy-consumption deployment of emergency UAV network for integrated communication-navigating-sensing by Li WANG, Qing WEI, Lianming XU, Yuan SHEN, Ping ZHANG, Aiguo FEI

“…In public emergencies such as accident relief, rescue workers are faced with challenges, such as poor communication, unstable navigating, and inaccurate disaster sensing.It is necessary to deploy an emergency unmanned aerial vehicle (UAV) network to guarantee the services of communication-navigating-sensing.Aiming at alleviating the problem of limited energy of UAV, a low-energy-consumption deployment of an emergency UAV network was first proposed for integrated communication-navigating-sensing (ICNS).The proposed scheme was able to realize network topology reconstruction and role cognition on demand.Then, a particle swarm algorithm based hierarchical matching decision-making algorithm was presented to jointly optimize three sub-problems, including the associations between UAVs and users, the resource allocation for multi-role UAV communications, and the UAV position.Simulation results show that the proposed ICNS scheme can achieve flexible adaptation of the multi-objective requirements and limited network resources, and dramatically reduce the demand for the number of UAVs and the deployment energy consumption.…”
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Computation offloading scheme for RIS-empowered UAV edge network by Bin LI, Wenshuai LIU, Wancheng XIE, Zesong FEI

“…In order to address the challenge of low offloading rate caused by the obstacles blocking in the links between unmanned aerial vehicle (UAV) and ground users (GU) in urban scene, a partial task offloading scheme for UAV-enabled mobile edge computing with the aid of reconfigurable intelligence surface was proposed.A nonconvex and multivariable coupling stochastic optimization problem was formulated by the joint design of the computation task allocation, the transmit power of GU, the phase shift of RIS, UAV computation resource, and UAV trajectory, aiming at maximizing the minimum average data throughput of GU.By leveraging the properties of mathematical expectation, the stochastic optimization problem was transformed into a deterministic optimization problem.Then, the deterministic optimization problem was decomposed into three subproblems by using the block coordinate descent (BCD) algorithm.By introducing auxiliary variables, the nonconvex problems were transformed into convex optimization problems via the successive convex approximation and semidefinite relaxation, and then the approximate suboptimal solution of the original problem was obtained.The simulation results show that the proposed algorithm has good convergence performance and effectively improves the average data throughput of GU.…”
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Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…Traditional methods, such as the Hungarian algorithm and greedy allocation, primarily focus on maximizing spectral efficiency, often neglecting fairness in resource distribution. …”
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A survey of task deployment and recovery in space-air-ground integrated networks based on SDN and NFV by CAO Yilu, JIA Ziye, YOU Jiahao, ZHANG Lei, WU Qihui

“…These challenges subsequently lead to issues such as the resource allocation, competition, and failure risks. …”
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Joint Demand Response and Task Offloading Strategy for 5G Edge Computing Network by Xu LU, Ying CHEN, Zhongping XU, Haiquan ZHANG, Chunfang MU, Kai CHEN, Yi SUN

“…To solve the Mixed Integer Non-linear Programming (MINLP) problem, this paper further proposes a Generalized Benders Decomposition (GBD) algorithm based on network scenario division. By decomposing the problem into a master problem of task offloading decision and a primal problem of charging/discharging and resource allocation , the complexity of the model is reduced. …”
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Analytical allocation of new construction methods based on future residential demand to modify residential construction efficiency plan by Majid Paziki, Mahdi Ravanshadnia

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Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty by Junjie Qiao, Xiaofang Meng, Weigang Zheng, Pengxue Huang, Tiefeng Xu, Yupeng Xu

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