A Fast Fault Location Based on a New Proposed Modern Metaheuristic Optimization Algorithm by Mohammad Parpaei, Hossein Askarian-Abyaneh, Farzad Razavi

“…Moreover, a fast and accurate modern metaheuristic optimization algorithm for this cost function is proposed, which are key parameters to estimate the fault location methods based on optimization algorithms. …”
Get full text

Improved Virtual Potential Field Algorithm Based on Probability Model in Three-Dimensional Directional Sensor Networks by Junjie Huang, Lijuan Sun, Ruchuan Wang, Haiping Huang

“…Furthermore, cross-set test is used to determine whether the sensory region has any overlap and coverage impact factor is introduced to reduce profitless rotation from coverage optimization, thereby the energy cost of nodes was restrained and the performance of the algorithm was improved. …”
Get full text

An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms by Saikat Banerjee, Abhoy Chand Mondal

“…The algorithm aims to find the most efficient path that includes all locations in a given set without revisiting any point. …”
Get full text

An Optimization Model for Production Scheduling in Parallel Machine Systems by Leting Zu, Wenzhu Liao, Xiaoxia Yang

“…A well-designed production scheduling scheme can significantly enhance manufacturing efficiency and reduce enterprise costs. This paper presents a tailored optimization model designed to address a more complex production scheduling problem that incorporates parallel machines and preventive maintenance. …”
Get full text

A design method of composite pixel-like antenna based on improved bald eagle search algorithm by WANG Yongqiang, LIU Bingqi, ZHU Bolin

“…This method not only retains the good convergence of the original algorithm, but also partially improves the global search ability. …”
Get full text

Study on optimization of Al6061 sphere surface roughness in diamond turning based on central composite design model and grey wolf optimizer algorithms by Le Thanh Binh, Duong Xuan Bien, Ngo Viet Hung, Chu Anh My, Hoang Nghia Duc, Nguyen Kim Hung, Bui Kim Hoa

“…This paper presents optimization results of the Al6061 surface roughness in turning ultra-precision based on the central composite design method (CCD) and the grey wolf optimization algorithm (GWO). …”
Get full text

Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…This aimed to optimize the Light Gradient-Boosting Machine (LightGBM) algorithm to enhance its performance and accuracy in the early detection of CHD, providing a reliable, cost-effective, and non-invasive diagnostic tool. …”
Get full text

Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. …”
Get full text

Optimal Pre-disaster and Post-disaster Scheduling of Mobile Energy Storage Considering the Influence of Transportation Network by XIE Peikun, LI Liang, SHI Yuanjie, SHENG Qing, LI Zhenkun

“…Furthermore， this strategy fully accounts for traffic flow changes in the transportation network， optimizes the selection of MES scheduling paths， reduces the negative impact of traffic congestion， and further improves the scheduling efficiency of the MES. …”
Get full text

Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
Get full text

Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
Get full text

Sequential Routing-Loading Algorithm for Optimizing One-Door Container Closed-Loop Logistics Operations by Paulina Kus Ariningsih, Titi Iswari, Kevin Djoenneady Poetra, Yoon Mac Kinley Aritonang

“…The improvement algorithm is tested in big data set with the input of the vehicle routing problem with time windows (VRP-TW) using the solution optimization of the Simulated Annealing process with restart point procedure (SA-R) for the routing optimization and Genetic Algorithm (GA) to optimize the container loading algorithm. …”
Get full text

Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network by Nandita Goyal, Munesh Chandra Trivedi

“…The proposed system makes a comparison of models with and without feature selection algorithms before applying the data to CNN. A comparison of different metaheuristics algorithms- Particle Swarm Optimization, Shuffled Frog Leap Optimization and Fire fly algorithm for feature optimization is done based on convergence rate and efficiency.…”
Get full text

QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems by Zuoqiang Du, Xingjie Li, Hui Li

“…Meanwhile, FJOSA employs a cross-layer optimization strategy that combines heuristic algorithms with cost functions to improve gate scheduling at a global level. …”
Get full text

Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm by Haichao Zhou, Zhen Jiang, Wenchao Li, Guolin Wang, Yongjie Tu

“…Test results of the rubber flow state indicated that the flow is regular and that warping disappears. The proposed optimization strategy can be used practically for improving the head runner design, shortening the product development cycle, and reducing the production cost.…”
Get full text

AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
Get full text

Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms by Somaye Imanpour, AhmadReza Montazerolghaem, Saeed Afshari

“…The findings from the simulations indicate that the proposed approach enhances the optimization and management of IoT networks, resulting in improved service quality, reduced operational costs, and increased productivity.…”
Get full text

Management of large energy storage power plants: optimization of charging and discharging with cuckoo search algorithm by Behnam Motalebinejad, Majid Hosseina, Mojtaba Vahedi, Mahmoud Samiei Moghaddam

“…This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. …”
Get full text

Optimizing Sentiment Analysis of Digital Wayang Viewer Comments using SMOTE and the Naïve Bayes Algorithm by mawar hardiyanti, Maria Karmelia Fajarlestari

Get full text

Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
Get full text