Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…This study addresses these challenges by optimizing load distribution through predicting employee capability using data-driven approaches, ensuring efficient resource utilization and enhanced productivity. Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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Dynamic Optimization of Tunnel Construction Scheduling in a Reverse Construction Scenario by Jianying Wei, Yuming Liu, Xiaochun Lu, Rong Zhao, Gan Wang

“…The Mixed-Integer Programming (MIP) approach is used to build the mathematical model, solved with both exact algorithms and Genetic Algorithms (GA), and implemented in Python 3.12.7. …”
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An analytical framework for regional integration development in the Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration using fuzzy clustering by Manchang Du

“…Collaboration and resource allocation will be maximized through the CUD-FCA, creating a more integrated and cost-effective urban agglomeration. …”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Accurate prediction of electricity price (EP) is crucial for energy utilities and grid operators for enhancing the energy trading, grid stability studies, resource allocations and pricing strategies, thereby improving the overall grid reliability, efficiency, and cost-effectiveness. …”
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Quantum-enhanced digital twin IoT for efficient healthcare task offloading by Ahmed K. Jameil, Hamed Al-Raweshidy

“…However, existing Digital Twin (DT)-based healthcare models suffer from high latency, inefficient resource allocation, cybersecurity vulnerabilities, and computational limitations when processing large-scale patient data. …”
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Traffic Classification in Software-Defined Networking Using Genetic Programming Tools by Spiridoula V. Margariti, Ioannis G. Tsoulos, Evangelia Kiousi, Eleftherios Stergiou

“…The classification of Software-Defined Networking (SDN) traffic is an essential tool for network management, network monitoring, traffic engineering, dynamic resource allocation planning, and applying Quality of Service (QoS) policies. …”
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DQN Simulation Model of Green Cooperative Market Behavior of Multi-Load Users for Optimal Evolution of New-Type Power System by ZHANG Shuo, YUAN Chunhui, LI Yingzi, XIAO Yangming, WEI Ming, HE Yunzheng

“…[Objective] To investigate and analyze the driving role of the green behavior of multiple loads on the evolution of a new type of power system and to enhance the flexibility and resource optimization allocation capacity of a new type of power system， this study conducted a simulation study of the green cooperative market behavior of multiple loads and constructed a simulation model of the green cooperative market behavior of multiple loads under the optimization of the evolution of a new power system. …”
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A Novel Performance Evaluation Framework for Sponge City Construction by Le Luo, Lei Yang, Wang Jiang

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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Dynamic scheduling strategies for cloud-based load balancing in parallel and distributed systems by Nasser S. Albalawi

“…The allocation step is followed by the Hybrid Ant Genetic Algorithm (HAGA), which is used to schedule tasks in parallel. …”
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Decision-Making Model for Life Cycle Management of Aircraft Components by Igor Kabashkin, Vitaly Susanin

“…The study contributes a scalable approach to predictive maintenance, balancing safety, cost, and resource allocation in dynamic operational environments.…”
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Application of expert systems in civil engineering by Ena Grčić, Marija Šperac

“…Artificial neural networks are effective in optimizing financial plans, estimating the duration of activities, assessing the productivity of work teams, and selecting contractors. Genetic algorithms find their application in resource allocation, selecting optimal solutions for task scheduling and project costs, as well as in building maintenance, while fuzzy logic aids in risk analysis, project management, and cost estimation. …”
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A Two-Stage Optimization Method for Multi-Runway Departure Sequencing Based on Continuous-Time Markov Chain by Guan Lian, Yingzi Wu, Weizhen Luo, Wenyong Li, Yaping Zhang, Xiaoyue Zhang

“…Then, continuous-time Markov chains (CTMC) were employed to track aircraft state transitions in the taxiway queue, and a nested whale optimization algorithm was proposed to optimize both the pushback sequence and runway resource allocation. …”
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A Mixed-Integer Linear Programming Model for Addressing Efficient Flexible Flow Shop Scheduling Problem with Automatic Guided Vehicles Consideration by Dekun Wang, Hongxu Wu, Wengang Zheng, Yuhao Zhao, Guangdong Tian, Wenjie Wang, Dong Chen

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Hybrid Disassembly Line Balancing of Multi-Factory Remanufacturing Process Considering Workers with Government Benefits by Xiaoyu Niu, Xiwang Guo, Peisheng Liu, Jiacun Wang, Shujin Qin, Liang Qi, Bin Hu, Yingjun Ji

“…The effectiveness and convergence of the algorithm are demonstrated through experiments on disassembly cases, with comparisons made to six peer algorithms and CPLEX. …”
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A method to manage the energy consumption of cloud centers for predictability in neuro-fuzzy networks by Ying Zhang

“…The proposed model leverages neuro-fuzzy networks for accurate workload predictions to achieve efficient real-time resource allocation and VM migration strategies that minimize energy waste. …”
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Wireless Channel Prediction Using Artificial Intelligence With Imperfect Datasets by Gowhar Javanmardi, Ramiro Samano Robles

“…One key objective of channel prediction is improving resource allocation to reduce latency and increase reliability, which are crucial metrics in applications such as autonomous vehicles. …”
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A GIS-based integrative approach for land use optimization in a semi-arid watershed by S.M. Tajbakhsh, H. Memarian, A. Kheyrkhah

“…In this study, five categories of land uses, i.e. irrigated orchard, rangeland, irrigated farming, rainfed farming and almond orchard were spatially optimized to minimize surface runoff and sediment yield and to increase net income by integrating three approaches: weighted goal programming, analytic hierarchy process and multi-objective land allocation algorithm. To achieve the target levels in this work, the acreages of almond orchard and rainfed farming should be reduced by 100% and 37.32% respectively, and irrigated farming acreage should be increased by 138.53%. …”
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Classification of start-ups’ digital marketing adoption experiences: an investigation of characteristics and interactions by Dina El-Shihy, Noha Hassan

“…Data were collected on the usage of digital marketing tools, level of utilization, duration of adoption, resource allocation, and budget. A nonparametric decision tree algorithm, visualized using R, was employed for data analysis. …”
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Construction and optimization of a smart classroom system for emotional computing by HUANG Lijuan, CHENG Zhengyi, YANG Ziyan

“…Secondly, to improve the performance of the smart classroom system, convex optimization theory was utilized to optimize the allocation of system resources. Finally, through verification, the multiple resources joint optimization method of the smart classroom system can effectively reduce the maximum delay of device data collection and processing, greatly improve the real-time performance of emotional computing in the smart classroom system, and avoid blindly pursuing the minimum average delay, effectively avoiding the situation where a single user experienced poorly due to poor real-time performance. …”
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