OPTIMIZING PROCESSOR WORKLOADS AND SYSTEM EFFICIENCY THROUGH GAME-THEORETIC MODELS IN DISTRIBUTED SYSTEMS by Merlan Telmanov, Zukhra Abdiakhmetova, Amandyk Kartbayev

“…Key results from this study highlight that while Nash Equilibrium fosters stability within the system, the adoption of optimal cooperative strategies significantly improves operational efficiency and minimizes transaction costs. …”
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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Ruiqin Duan, Xiaosheng Peng, Cong Li, Zimin Yang, Yan Jiang, Xiufeng Li, Shuangquan Liu

“…Wind power prediction (WPP) is necessary to the safe operation and economic dispatch of power systems. In order to improve the prediction accuracy of WPP, in this paper we propose a three-step model named SDAE-SVR-BA to be applied in short-term WPP based on stacked-denoising-autoencoder (SDAE) feature processing, bat algorithm (BA) optimization and support vector regression (SVR). …”
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Optimization of vehicle routing problems combining the demand urgency and road damage for multiple disasters by Ran Li, Xiaofei Ye, Shuyi Pei, Xingchen Yan, Tao Wang, Jun Chen, Pengjun Zheng

“…A set of evaluation index systems for multiple disasters was established to quantify the urgency of demand. The routing optimization model of emergency vehicles for multiple disasters was proposed by combining demand urgency and road damage, and the non-dominated sorting genetic algorithm II (NSGA-II) was used to simulate and validate the model. …”
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Optimization of Fresh Food Logistics Routes for Heterogeneous Fleets in Segmented Transshipment Mode by Haoqing Sun, Manhui He, Yanbing Gai, Jinghao Cao

“…The k-means++ clustering algorithm is used to determine transshipment points, while an improved adaptive multi-objective ant colony optimization algorithm (IAMACO) is employed to optimize the delivery routes for the heterogeneous fleet. …”
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Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking by Athanasios Sidiropoulos, Dimitrios Bechtsis, Dimitrios Vlachos

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A Novel Back Propagation Neural Network Based on the Harris Hawks Optimization Algorithm for the Remaining Useful Life Prediction of Lithium-Ion Batteries by Yuyang Zhou, Zijian Shao, Huanhuan Li, Jing Chen, Haohan Sun, Yaping Wang, Nan Wang, Lei Pei, Zhen Wang, Houzhong Zhang, Chaochun Yuan

“…In order to achieve accurate and reliable RUL prediction, a novel RUL prediction method which employs a back propagation (BP) neural network based on the Harris Hawks optimization (HHO) algorithm is proposed. This method optimizes the BP parameters using the improved HHO algorithm. …”
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Integrating AI Deep Reinforcement Learning With Evolutionary Algorithms for Advanced Threat Detection in Smart City Energy Management by Fenghua Liu, Xiaoming Li

“…The results from simulated smart city environments demonstrate significant improvements in energy efficiency, cost reduction, and emission control. …”
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Multi-energy System Planning and Configuration Study for Low-Carbon Parks Based on Comprehensive Optimization Objectives by Yang WANG, Fei LU, Ji LI, Zhukui TAN, Zongyu SUN, Wei XU, Zihong SONG, Zhenpeng LIU

“…Secondly, by taking a multi-energy system with triple supply of cooling, heating and power system coupled with ground source heat pump, energy storage, and gas boiler in a typical low-carbon park as an example, a comparative analysis was made on the configuration results and optimization speed with different optimization algorithms, and a study was conducted on the impacts of different optimization objectives such as optimal comprehensive optimization objective and lowest whole life-cycle cost and energy consumption on the capacity optimization configuration results and typical daily operation situation. …”
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A genetic algorithm-based solution for multi-type maximal covering location problem (MMCLP): application to defense and deterrence by J.D. Lessan, Geoff Pond

“…Design/methodology/approach – In our case study, we use open source geographic and demographic data from Canadian sources as inputs to our optimization problem. Due to the complexity of the MIP formulation, we propose a hybrid metaheuristic solution approach, for which a genetic algorithm (GA) is proposed and integrated with local and large neighborhood search operators. …”
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Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

“…So, this study integrates the ANFIS (adaptive neuro-fuzzy inference system) and ELM (extreme learning machine) machine learning models with three optimization algorithms, i.e., WCA (water cycle algorithm), PSO (particle swarm optimization), and GWO (grey wolf optimizer) to precisely estimate the CS of fiber-reinforced concrete (FRC) containing SiO2. …”
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Optimization of Home Energy Management Systems in Smart Cities Using Bacterial Foraging Algorithm and Deep Reinforcement Learning for Enhanced Renewable Energy Integration by Mohammed Naif Alatawi

“…Significant reductions in total energy consumption and cost, accompanied by improved peak demand management, exemplify the algorithms’ impact. …”
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Microservice Workflow Scheduling with a Resource Configuration Model Under Deadline and Reliability Constraints by Wenzheng Li, Xiaoping Li, Long Chen, Mingjing Wang

“…Experiments on four scientific workflow datasets show that the proposed approach achieves an average cost reduction of 44.59% compared to existing reliability scheduling algorithms, with improvements of 26.63% in the worst case and 73.72% in the best case.…”
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A new stochastic multi-objective model for the optimal management of a PV/wind integrated energy system with demand response, P2G, and energy storage devices by Hossein Faramarzi, Navid Ghaffarzadeh, Farhad Shahnia

“…Optimal energy hub scheduling (EHS) has emerged as a promising strategy for improving the efficiency and flexibility of power systems. …”
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Optimization for Express/Local Train Stop Plans on City Rapid Rail Transit Lines by GUO Jingfan

“…Although the algorithm slightly increases operational costs for enterprises, it significantly reduces passenger travel time costs and improves overall passenger travel accessibility.…”
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Optimized Support Vector Machine Assisted BOTDA for Temperature Extraction With Accuracy Enhancement by Hongna Zhu, Lei Yu, Yufeng Zhang, Le Cheng, Zhenyu Zhu, Jiayin Song, Jinli Zhang, Bin Luo, Kai Yang

“…In addition to the enhanced accuracy with good robustness, the optimized algorithms have faster processing speed than the curve fitting method, over 20-times improvement. …”
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Maximizing efficiency and performance of water distribution systems through the implementation of optimization algorithms: A comprehensive analysis of valve and chlorine booster pl... by Mohamadreza Najarzadegan, Mehrtash Eskandaripour

“…By employing advanced optimization algorithms, specifically the Genetic Algorithm (GA) and Slime Mould Algorithm (SMA), the research identifies optimal configurations across two benchmark networks, Jowitt and Xu and GoYang. …”
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Research on the configuration scheme and system parameter optimization of pumps in the component cooling system and sea water system for HPR1000 by Weiguang Zhao, Pei Yu, Xiaobo Zeng, Guangming Fan, Zhaoming Meng, Changqi Yan

“…Based on a mathematical model for CCS and SWS that can be utilized for optimization calculations, we propose and validate an Improved Non-dominated Sorting Genetic Algorithm II (INSGA-II) with good algorithm performance, optimizing for system design costs and total operational costs as objectives, and provide a sensitivity analysis of relevant variables. …”
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Autonomous UAV Path Optimization Using Genetic and Multiobjective Evolutionary Algorithms for Effective Data Retrieval in Cache-Enabled Mobile Ad-Hoc WSNs by Umair B. Chaudhry, Chris Ian Phillips

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Enhanced Reinforcement Learning Algorithm Based-Transmission Parameter Selection for Optimization of Energy Consumption and Packet Delivery Ratio in LoRa Wireless Networks by Batyrbek Zholamanov, Askhat Bolatbek, Ahmet Saymbetov, Madiyar Nurgaliyev, Evan Yershov, Kymbat Kopbay, Sayat Orynbassar, Gulbakhar Dosymbetova, Ainur Kapparova, Nurzhigit Kuttybay, Nursultan Koshkarbay

“…The proposed approach demonstrates the best performance, achieving a 17.2% increase in the packet delivery ratio compared to the traditional Adaptive Data Rate (ADR) algorithm. The proposed DDQN-PER algorithm showed PDR improvement in the range of 6.2–8.11% compared to other existing RL and machine-learning-based works.…”
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Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment by Eunmok Yang, Sooyong Jeong, Changho Seo

“…Besides, the feature pruning process is performed using an improved pelican optimization algorithm (IPOA), which enables the choice of an optimal subset of features. …”
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