Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…The simulation results show that the neural network model can be applied to the prediction of stratospheric wind field and the BP neural networks optimized by genetic algorithm and particle swarm optimization can greatly improve the prediction accuracy of BP neural network, and the forecast wind speed is following the true value in a certain period of time. …”
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Optimizing Crop Yield Prediction: An In-Depth Analysis of Outlier Detection Algorithms on Davangere Region by C. S. Anu, C. R. Nirmala, A. Bhowmik, A. Johnson Santhosh

“…This method demonstrated improved performance in refining the crop yield prediction model by identifying and removing outliers, thereby contributing to more accurate predictions and optimized planning in the dynamic landscape of the Davangere region.…”
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Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…To meet the personalized distribution needs of customers, comprehensively consider customer value, the urgency of customer needs, and the impact of priority distribution to the customer on the enterprise, and based on regional restrictions, put forward vehicle-drone joint distribution path optimization problem considering customer priority. First, the goal is to minimize the sum of total distribution cost and customer priority cost integrating soft time windows and constructing a path optimization model of the vehicle-drone joint distribution. …”
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Multi-objective optimization of dual-stator permanent magnet motor based on composite algorithm by Xiaoguang Kong, Zhuo Yang

“…Then, the Taguchi method optimizes the significant variables, the genetic algorithm based on the Kriging response surface model optimizes the non-significant variables, and finally, the optimal solution is selected on the Pareto front. …”
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A Distributed Optimization Algorithm for Energy of Wireless Sensor Networks Based on Potential Game by Lingfeng Shao, Junjie Yang, Jicheng Fang

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Enhancing computational efficiency in solving Knapsack problem: insights from algorithmic parallelization and optimization by Bashar Bin Usman, Okeyinka Aderemi Elisha, Ibrahim Abdullahi, Idris Rabiu, Adamu Isah, Abdulganiyyu Abdulrahman

“…Hence, the application of approximate algorithms is usually considered when encountering this optimization problem. …”
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Optimization of the control system of BP-PID rice polishing unit based on WAO algorithm by HUANG Jinliang, ZHOU Jin, YU Wei

“…ObjectiveAddress the current issues of poor internal flow stability, low single-machine efficiency, and subpar polishing quality in rice polishing units.MethodsFirstly, the traditional polishing machine was improved, its control parameters were clarified, and the mathematical model of the rice polishing unit was established. …”
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Distributed Photovoltaic Power Energy Generation Prediction Based on Improved Multi-objective Particle Algorithm by Yuanzheng Xiao, Huawei Hong, Feifei Chen, Xiaorui Qian, Ming Xu, Hanbin Ma

“…A hybrid LSTM-PSO model was created, where the LSTM network served as the core prediction model, and the improved MO-PSO algorithm optimized its hyperparameters, enhancing generalization and avoiding overfitting. …”
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Power grid energy storage system planning method based on optimized butterfly algorithm by Xiang Yin, Xiaojun Zhang, Fuhai Cui

“…Abstract In response to the power supply security of power grid system caused by a large number of clean energy connected to the distribution network, based on the grid side energy storage investors, the butterfly optimization algorithm is improved by combining the dynamic switching probability coordination algorithm and the dynamic Gaussian mutation strategy. …”
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Fog node intrusion detection and response based on SVMIF and INSGA-II algorithm by Zhuojun Luo

“…Additionally, modified particle swarm optimization was employed to optimize the model's parameters. …”
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Gradual Optimization of University Course Scheduling Problem Using Genetic Algorithm and Dynamic Programming by Xu Han, Dian Wang

“…To improve the computational efficiency and solution quality, a hybrid method combining a genetic algorithm and dynamic programming, named POGA-DP, was designed. …”
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Improved UAV Target Detection Model for RT-DETR by Yong He, Yufan Pang, Guolin Ou, Renfeng Xiao, Yifan Tang

“…In light of the shortcomings pertaining to UAV small target detection, the detection of complex scenes, and the detection of multi-scale targets, a time-frequency dual-domain feature extraction algorithm, TF-DETR, has been proposed. This algorithm has been optimized for RT-DETR.Firstly, a time-frequency domain feature extraction module, TF-CSPNet, has been introduced into the backbone network. …”
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Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting by Yumeng Zhu, Qi Zhu

“…The joint optimization problem is divided into three subproblems, which use the Lagrange multiplier method, a simulated annealing algorithm, and a particle swarm optimization algorithm. …”
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Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm. by Ali Bahrami, Morteza Rakhshaninejad, Rouzbeh Ghousi, Alireza Atashi

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Energy Efficiency and Reliability in Underwater Wireless Sensor Networks Using Cuckoo Optimizer Algorithm by M. Dosaranian-Moghadam, Z. Amo-Rahimi

“…In the proposed algorithm, by presenting a cost function in COA algorithm, a hop-by-hop method of route selection is performed using power consumption and energy content of the current node; while in Greedy Geographic Forwarding based on Geospatial Division (GGFGD) algorithm, data transfer is based on the closest route to a destination criterion. …”
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A FPGA Accelerator of Distributed A3C Algorithm with Optimal Resource Deployment by Fen Ge, Guohui Zhang, Ziyu Li, Fang Zhou

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Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer by Zuriani Mustaffa, Mohd Herwan Sulaiman, Muhammad ‘Arif Mohamad

“…To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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Deep deterministic policy gradient-based energy efficiency optimization algorithm for CR-NOMA by ZHANG Yun

“…Therefore, for CR-NOMA, deep deterministic policy gradient-based energy efficiency optimization (DPEE) algorithm was proposed. By jointly optimizing the transmission power and time slot splitting coefficient, the energy efficiency of sensor devices was improved. …”
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Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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