Research on Reactive Power Optimization Strategy under the Intelligent Improvement Model of the Distribution Network by Menglin Yu

“…In order to improve the reactive power optimization effect of the distribution network, this paper combines the multiagent deep reinforcement learning algorithm to analyze the reactive power optimization strategy of the distribution network and constructs an intelligent optimization model. …”
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Dynamics of traffic flow in lattice model by GUO Wei-ping, WANG Xiao-fan, LI Xiang

“…Based on the lattice network model,three factors affecting the efficiency of network traffic were investigated: routing algorithm,router performance and user’s strategy,and three alternatives to improve the efficiency of communica-tion network traffic were further figured: chose different routing variable according to the loads of the network,made use of advanced routing equipments and adjusted the creation probability of data in the light of users’ feedback strategy.…”
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Research on pose estimation algorithm of non-cooperative target tracked vehicles based on PnP model by Zhigang Ren, Xinagjun Tang, Guoquan Ren, Dinghai Wu

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A novel time difference of arrival localization algorithm using a neural network ensemble model by Zhenkai Zhang, Feng Jiang, Boyuan Li, Bing Zhang

“…The simulation results show that the proposed algorithm is efficient in improving the generalization ability and localization precision of the neural network ensemble model.…”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“… In view of the difficulty of snow leopard detection and recognition in infrared camera images, a snow leopard detection algorithm is proposed based on EfficientDet, which combines domain migration and new attention mechanism.Firstly, the algorithm adopts image enhancement to expand the training sample and adds non-snow leopard images to optimize the dataset structure to improve the robustness of the model. …”
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Improving Modularity Regularization Techniques for Estimating Structures in Complex Network by Samaa F. Ibraheem, Basad Al-Sarray

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Prediction of Mechanical Properties of Cotton Fibers by a BP Neural Network Model Optimized by Genetic Algorithm by Junyang Wang, Limin Zhang, Xiang Liu, Jinchan Zhang, Wanxin Wang, Hong Xu

“…Finally, the improved model was evaluated using the same dataset. …”
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A Water Quality Prediction Model Based on Long Short-Term Memory Networks and Optimization Algorithms by Aihua Yu, Qingjie Xiao

“…In comparison with the previous prediction models such as SVR, LSTM, CNN-LSTM and CNN-GRU, obviously, the prediction effect of AWPSO-LSTMAT is significantly improved by means of modifying and optimizing the original algorithm. …”
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Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm by Shuang Gan, Heng Hu, Shaoshuai Li, Qian Peng, Taidong Yan, Huasheng Gong, Yuancheng Zhang

“…The proposed solution integrates the Kepler Optimization Algorithm (KOA) with the Gaussian Quantum Improved Particle Swarm Optimization (GQPSO) to address multi-objective optimization, with the goal of maximizing power generation, minimizing operational costs, and enhancing system stability. …”
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Development of Hybrid Optimization Model Using Grey-ANFIS-Jaya Algorithm for CNC Drilling of Aluminium Alloy by Katta Lakshmi Narasimhamu, Manikandan Natarajan, Pasupuleti Thejasree, Emad Makki, Jayant Giri, Neeraj Sunheriya, Rajkumar Chadge, Chetan Mahatme, Pallavi Giri, T. Sathish

“…Statistical error analysis is used to estimate the performance of the established optimization model. Based on the investigative outcomes, the best-suited process variable combinations will be used to provide improved and enhanced multiperformance characteristics.…”
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Optimizing anomaly detection models for edge IIoT with an enhanced firefly algorithm-based hyperparameter tuning strategy by Mohemmed Yousuf Rahamathulla, Mangayarkarasi Ramaiah

“…This work presents an Enhanced Firefly Algorithm (EFA) for optimizing the hyperparameters of ML models to enable effective and accurate threat detection in resource-constrained IIoT contexts, so addressing these challenges. …”
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First-principle modeling of parallel-flow regenerative kilns and their optimization with genetic algorithm and gradient-based method by Michael Kreitmeir, Bruno Villela Pedras Lago, Ladislaus Schoenfeld, Sebastian Rehfeldt, Harald Klein

“…Finally, we use a genetic algorithm to optimize the feed mass flows such that the conversion and the fuel efficiency are improved in a Pareto-optimal manner. …”
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Advances to IoT security using a GRU-CNN deep learning model trained on SUCMO algorithm by Amit Sagu, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, Piyush Kumar Shukla, Mohd Asif Shah

“…The SUCMO algorithm fine-tunes the deep learning model’s hyperparameters to improve classification accuracy. …”
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Leveraging retinanet based object detection model for assisting visually impaired individuals with metaheuristic optimization algorithm by Alaa O. Khadidos, Ayman Yafoz

“…This paper proposes a novel Object Detection Model for Visually Impaired Individuals with a Metaheuristic Optimization Algorithm (ODMVII-MOA) technique. …”
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Behavioral Modeling of SiC MOSFET Static and Dynamic Characteristics Based on Particle Swarm Optimization Algorithm by Zhibo Zhu, Yang Zhao, Wei Yan

“…The PSO algorithm is used to extract the parameters of the improved Enz-Krummnacher-Vittoz model and a static characteristic behavioral model of the SiC MOSFET is established, avoiding a large amount of simulation or calculation time for circuit and datasheet-drive models, the efficiency is increased by 60%, and the model accuracy is 98% compared to the datasheet. …”
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Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model by Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

“…However, the model accuracy and precision can change according to the model structure (hyperparameters, algorithms, epoch) and data characteristics. …”
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Improved sub-band JND model with textural decomposition and its application in perceptual image coding by Ming-kui ZHENG, Kai-xiong SU, Wei-xing WANG, Cheng-dong LAN, Xiu-zhi YANG

“…In order to improve the accuracy of the just noticeable difference (JND) model in transform domain, an en-hanced JND model with a new method for contrast masking factor estimation was proposed. …”
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SMOTE vs. SMOTEENN: A Study on the Performance of Resampling Algorithms for Addressing Class Imbalance in Regression Models by Gazi Husain, Daniel Nasef, Rejath Jose, Jonathan Mayer, Molly Bekbolatova, Timothy Devine, Milan Toma

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Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model by Lokesh Selvaraj, Balakrishnan Ganesan

“…In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. …”
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Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm by Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb

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