A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment by Joelle Kabdjou, Norihiko Shinomiya

“…Using a Long Short-Term Memory (LSTM) algorithm optimized by Super SAPSO (Simulated Annealing Particle Swarm Optimization), the model forecasts server failures with improved accuracy, reducing False Alarm Rates and improving Failure Detection Rates. …”
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Numerical thermodynamic-economic study and machine learning-based optimization of an innovative biogas-driven integrated power plant combined with sustainable liquid CO2 and liquid... by Ruijia Yuan, Fan Shi, Azher M. Abed, Mohamed Shaban, Sarminah Samad, Ahmad Almadhor, Barno Abdullaeva, Mouloud Aoudia, Salem Alkhalaf, Samah G. Babiker

“…In industrial environments, it effectively optimizes energy use and production processes by examining various operational factors, which leads to cost reductions and improved efficiency via predictive maintenance and cohesive energy strategies. …”
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Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives by Nuno Souza e Silva, Paulo Ferrão

“…Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. …”
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Low-cost Cascaded prototype for DC-DC converters for Renewable energy applications by Rerhrhaye Fathallah, Ennaciri Yassine, Rerhrhaye Badr, Lahlouh Ilyas, Khouili Driss, El Martaoui Chaymae, El Akkary Ahmed, Sefiani Nacer

“…The proposed prototype offers a cost-effective and highly efficient solution for implementing various Maximum Power Point Tracking (MPPT) algorithms and advanced control methods. …”
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Anchor Dragging Risk Estimation Strategy from Supervised Cost-Sensitive Learning by Sang-Lok Yoo, Shem Otoi Onyango, Joo-Sung Kim, Kwang-Il Kim

“…This suggested that the optimal ML strategy would involve undersampling the majority class and cost-sensitive learning. …”
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Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks by Jiagao Wu, Yue Ma, Linfeng Liu

“…In this article, we present a network model of the multi-community delay-tolerant networks and formulate a dynamic quota-controlled routing problem of minimizing the average number of copies of a message that satisfies the required delivery probability under the given time-to-live of the message as a nonlinear optimization problem. To solve this problem, we propose an improved genetic algorithm called genetic algorithm for delivery probability and time-to-live optimization for the dynamic quota-controlled routing scheme to reduce the routing cost further. …”
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A Robust Multi-Objective Evolutionary Framework for Artificial Island Construction Scheduling Under Dynamic Constraints by Tianju Zheng, Liping Sun, Mingwei Li, Guangyao Yuan, Shuqi Li

“…Artificial island construction is a multifaceted engineering endeavor that demands precise scheduling to optimize resource allocation, control costs, ensure safety, and minimize environmental impact within dynamic marine environments. …”
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Hardware implementation of RSA encryption algorithm based on pipeline by Yang Longfei, Lu Shi, Peng Kuang

“…To address the high cost of implementing long-bits RSA encryption algorithms in hardware, improvements have been made to the traditional radix-4 Montgomery algorithm. …”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno–economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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Enhancing stochastic optimal power flow with modified cheetah optimizer for integrating renewable energy sources by Majid Saeidi, Taher Niknam, Mohsen Zare, Zulfiqar Ali Memon

“…A backward-forward correction method was used to correct errors in three types of reserves, improving the solution quality. The effectiveness of the MCO in solving practical large-scale optimization problems was demonstrated by the results of the 10-unit and 30-unit dynamic economic dispatch, achieving lower cost values than previously published papers. …”
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Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

“…The experimental results show that compared to the single skill model, this model can effectively shorten project duration, reduce human resource costs, and improve skill scores. For example, in a specific experimental dataset, when the project duration is limited to 200 h, the most suitable labor duration for the plan is 193.8 h, the human resource cost is 7493 yuan, and the skill score is improved by 268. …”
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A Bat Algorithm with Mutation for UCAV Path Planning by Gaige Wang, Lihong Guo, Hong Duan, Luo Liu, Heqi Wang

“…Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. …”
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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The proposed ECE-VDT system encompasses an optimized SimYOLO-V5s algorithm and its five variants for vehicle detection, while the optimized deep-SORT algorithm is proposed for vehicle tracking. …”
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An intelligent hybrid grey wolf-particle swarm optimizer for optimization in complex engineering design problem by Muhammad Suhail Shaikh, Haoyue Lin, Senlin Xie, Xiaoqing Dong, Yifan Lin, Chandan Kumar Shiva, Wulfran Fendzi Mbasso

“…The improvement in the average best optimal value varies across different cases, demonstrating the effectiveness of the proposed method. …”
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A Multi-Objective Particle Swarm Optimization Approach for Optimizing K-Means Clustering Centroids by Aina Latifa Riyana Putri, Joko Riyono, Christina Eni Pujiastuti, Supriyadi

“…This study evaluates the performance of the standard K-Means algorithm and proposes a Multiobjective Particle Swarm Optimization K-Means (MOPSO+K-Means) approach to improve clustering accuracy. …”
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Development of Low-Cost Single-Chip Automotive 4D Millimeter-Wave Radar by Yongjun Cai, Jie Bai, Hui-Liang Shen, Libo Huang, Bing Rao, Haiyang Wang

“…This study focuses on developing single-chip 4D automotive millimeter-wave radar, covering system architecture design, antenna optimization, signal processing algorithm creation, and performance validation. …”
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Future Smart Grids Control and Optimization: A Reinforcement Learning Tool for Optimal Operation Planning by Federico Rossi, Giancarlo Storti Gajani, Samuele Grillo, Giambattista Gruosso

“…This study presents a methodology based on reinforcement learning (RL) for evaluating optimal power flow with respect to various cost functions. …”
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Optimal Temperature Calculation for Multicriteria Optimization of the Hydrogenation of Polycyclic Aromatic Hydrocarbons by NSGA-II Method by A. A. Alexandrova, S. N. Koledin

“…Introduction. Multicriteria optimization, taking into account contradicting criteria, is used to improve production efficiency, reduce costs, improve product quality and environmental safety of processes. …”
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Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders. by Zuhair Alaas, Ghareeb Moustafa, Hany Mansour

“…The PO is a novel bio-inspired optimization algorithm that draws inspiration from pelicans' intelligence and behavior which incorporates unique methods for exploration and exploitation, improving its effectiveness in various optimization challenges. …”
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A Novel Tornado Detection Algorithm Based on XGBoost by Qiangyu Zeng, Guoxiu Zhang, Shangdan Huang, Wenwen Song, Jianxin He, Hao Wang, Yin Liu

“…In addition, the TDA-XGB algorithm combines artificial intelligence-assisted learning to optimize the traditional algorithm based on the tornado vortex signature (TVS) and tornado debris signature (TDS), further improving the detection effect. …”
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