Multi-objective Optimization Configuration of Capacitor Blocking Devices Based on Field-Circuit Coupled Model and Improved Differential Evolution Algorithm by Hongwei LIU

“…Based on the operating characteristics of the DC blocking devices, this paper analyzes the influence of the DC blocking devices on the DC current near the neutral point of the transformers, and proposes a multi-objective optimization configuration method for capacitor blocking devices based on the field-circuit coupling model and improved differential evolution algorithm. …”
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Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations by Marzieh Faridi Masouleh, Ali Harounabadi, Asal Sayyad

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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters by Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu

“…The primary goal is to improve hyperparameter tuning performance in deep learning models compared to conventional methods such as Bayesian Optimization and Random Search. …”
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Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

“…A load flow and short circuit analysis is performed on the designed transmission system for a number of critical scenarios. The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
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Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm by M. H. Zhang, X. Feng, M. Bano, C. Liu, Q. Liu, X. Wang

“…Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. …”
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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…It also shows that the algorithm improves the generalization ability and performance of the model.…”
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Enhancing PM_2.5 Air Pollution Prediction Performance by Optimizing the Echo State Network (ESN) Deep Learning Model Using New Metaheuristic Algorithms by Iman Zandi, Ali Jafari, Aynaz Lotfata

“…This study evaluates efficient metaheuristic algorithms for optimizing deep learning model hyperparameters to improve the accuracy of PM_2.5 concentration predictions. …”
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Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique by Md Moktarul Alam, Richard Perdriau, Mohammed Ramdani, Mohsen Koohestani

“…This paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. …”
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AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…However, most existing methods rely on static or rule-based models, which lack the flexibility to handle fluctuating flow rates, variable environmental loads, and unforeseen disruptions. …”
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Improved Particle Swarm Optimization Algorithm Optimize the Control Strategy of Family Energy Management System by WEI Qi, LI Shi-nan, ZHU Ying-ying

“…In order to better respond accding to the demand of TOU price control project management of family family load and energy，put forward the household electricity load control strategy，based on analysis of the existing household electricity load control strategies，using improved particle swarm optimization algorithm for the control strategy optimization target，the establishment of a single-user，multi-user household electricity control optimization model，In the MATLAB platform，the results of optimization algorithm are analyzed by simulation. …”
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Dynamic Path Optimization Based on Improved Ant Colony Algorithm by Juan Cheng

“…Aiming at the shortcomings of the current dynamic path optimization method, the improved ant colony algorithm was used to optimize the dynamic path. …”
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Using BERT and ZFNet/ELM optimized by improved Orca optimization algorithm for sentiment analysis by Jun Yang, Jafar Safarzadeh

“…Then, the data were inserted into ZFNet/ELM, which was optimized by Improved Orca Optimization Algorithm (IOPA). …”
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Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm by Yuhao Wang, Yi Wang, Bin He

Subjects: “…improved NSGA-III algorithm…”
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Multi-objective programming method for ship weather routing based on fusion of A* and NSGA-II by Yuankui LI, Jiyuan SUO, Dongye YU, Xinyu ZHANG, Fang YANG, Xuefeng YANG

“…ResultsThe simulation results demonstrate that the proposed model and algorithm can obtain a uniformly distributed and diversified Pareto optimal route set. …”
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Proposing an Improved Version of the Bat Algorithm by Davar Giveki, Javad Ebrahimi, Maryam Sarshar

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A hybrid machine learning model with self-improved optimization algorithm for trust and privacy preservation in cloud environment by Himani Saini, Gopal Singh, Sandeep Dalal, Iyyappan Moorthi, Sultan Mesfer Aldossary, Nasratullah Nuristani, Arshad Hashmi

“…The model combines k-anonymity for user privacy, an optimized Firefly algorithm for trust generation, and a Time-aware Modified Best Fit Decreasing (T-MBFD) algorithm to improve resource allocation efficiency. …”
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Spiking Neural Networks Optimized by Improved Cuckoo Search Algorithm: A Model for Financial Time Series Forecasting by Panke Qin, Yongjie Ding, Ya Li, Bo Ye, Zhenlun Gao, Yaxing Liu, Zhongqi Cai, Haoran Qi

“…To address the performance limitations of Spiking Neural Networks (SNNs) caused by hyperparameter sensitivity, this study proposes an SNN model optimized by an Improved Cuckoo Search (ICS) algorithm (termed ICS-SNN). …”
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Research on the application of a model combining improved optimization algorithms and neural networks in trajectory tracking of robotic arms by Yanhui Lai, Zuobing Chen, Ya Mao

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