Based on PCA and SSA-LightGBM oil-immersed transformer fault diagnosis method. by Jizhong Wang, Jianfei Chi, Yeqiang Ding, Haiyan Yao, Qiang Guo

“…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”
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Simulation of incremental update of electronic document information based on big data technology by Zhiyuan Jin, Qi Zhang, Tiejun Pan

“…The network structure optimization is mainly achieved by increasing the number of neurons in the hidden layer, and the BP algorithm and gradient descent method are used to iteratively calculate until the model converges, so as to improve the model’s ability to capture the dynamic features of incremental data. …”
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An adaptive video stream transmission control method for wireless heterogeneous networks based on A3C by Zhiqiang LUO, Wei WANG, Xiaorong ZHU

“…The adaptive bit rate (ABR) algorithm has become the focus research in video transmission.However,due to the characteristics of 5G wireless heterogeneous networks,such as large fluctuation of channel bandwidth and obvious differences between different networks,the adaptive video stream transmission with multi-terminal cooperation was faced with great challenges.An adaptive video stream transmission control method based on deep reinforcement learning was proposed.First of all,a video stream dynamic programming model was established to jointly optimize the transmission rate and diversion strategy.Since the solution of this optimization problem depended on accurate channel estimation,dynamically changing channel state was difficult to achieve.Therefore,the dynamic programming problem was improved to reinforcement learning task,and the A3C algorithm was used to dynamically determine the video bit rate and diversion strategy.Finally,the simulation was carried out according to the measured network data,and compared with the traditional optimization method,the method proposed better improved the user QoE.…”
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Prediction of Transformer Residual Flux Based on J-A Hysteresis Theory by Qi Long, Xu Yang, Keru Jiang, Changhong Zhang, Mingchun Hou, Yu Xin, Dehua Xiong, Xiongying Duan

“…It has low dependence on the initial conditions and greatly avoids the influence of DC offset and noise on measurement results. Firstly, an improved particle-swarm optimization algorithm is proposed in this paper to address the problem of slow convergence speed and susceptibility to local optima in current particle-swarm optimization algorithms for extracting J-A model parameters. …”
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Research on deep reinforcement learning in Internet of vehicles edge computing based on Quasi-Newton method by ZHANG Jianwu, LU Zetao, ZHANG Qianhua, ZHAN Ming

“…To address the issues of ineffective task offloading decisions caused by multitasking and resource constraints in vehicular networks, the Quasi-Newton method deep reinforcement learning dual-phase online offloading (QNRLO) algorithm was proposed. The algorithm was designed by initially incorporating batch normalization techniques to optimize the training process of deep neural networks. …”
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A Bicriteria Approach Identifying Nondominated Portfolios by Javier Pereira, Broderick Crawford, Fernando Paredes, Ricardo Soto

“…In order to improve the former algorithm, a process finding an optimal solution of a monocriteria version of this problem is proposed, which is further used as a first feasible solution aiding to find nondominated solutions more rapidly. …”
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Estimation of Cement Asphalt Mortar Disengagement Degree Using Vehicle Dynamic Response by Hui Shi, Liqiang Zhu, Hongmei Shi, Zujun Yu

“…An improved genetic algorithm with a shifting window is employed for the parameter optimization, which is split into a number of phases and whose initial values are given in terms of a priori probabilities. …”
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LIGHTWEIGHT OF THE VEHICLE B PILLAR BASED ON SIX SIGMA ROBUST DESIGN UNDER SIDE IMPACT by QIU RuiBin, CHEN Yuan, LEI Fei, YANG ShaoYong, LI YongJun

“…In this paper,by considering uncertainty factors,taking side impact of a car as an example,first of all,an accurate finite element model is established and verified according to relevant crash regulations,then,after building an approximate model and a deterministic optimization model,the optimal solution is obtained by sequential quadratic programming algorithm and the reliability analysis is used,finally the original vehicle B pillar is accomplished lightweight research and improvement by using six sigma robust design method. …”
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Adaptive robust position control scheme for an electromagnetic levitation system with experimental verification. by Ziwei Wu, Kuangang Fan, Ping Yi

“…Firstly, a nonlinear model of the electromagnetic levitation ball system was established; Secondly, robust sliding mode control is combined with linear active disturbance rejection control, and an adaptive parameter tuning strategy is introduced for the PD module in LADRC; Meanwhile, an improved whale optimization algorithm was proposed to address the issue of excessive adjustable parameters in the controller; In addition, the stability and convergence of the control algorithm were proven using the Lyapunov equation; Finally, in order to verify the effectiveness of the control method, PID, LADRC, CS-LADRC, and I-LADRC were introduced for simulation analysis and experimental verification. …”
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Research on Obstacle-Avoidance Trajectory Planning for Drill and Anchor Materials Handling by a Mechanical Arm on a Coal Mine Drilling and Anchoring Robot by Siya Sun, Sirui Mao, Xusheng Xue, Chuanwei Wang, Hongwei Ma, Yifeng Guo, Haining Yuan, Hao Su

“…Finally, a simulation environment was built in a ROS environment to compare and analyze the planning effect of different algorithms. The simulation results showed that the improved Bi-RRT trajectory planning algorithm incorporating the artificial potential field improved the optimization speed by 69.8% and shortened the trajectory length by 46.6% compared with the traditional RRT algorithm.…”
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Deep Reinforcement Learning for UAV Intelligent Mission Planning by Longfei Yue, Rennong Yang, Ying Zhang, Lixin Yu, Zhuangzhuang Wang

“…Then, the SEAD intelligent planning model based on the proximal policy optimization (PPO) algorithm is established and a general intelligent planning architecture is proposed. …”
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Research on collaborative scheduling strategies of multi-agent agricultural machinery groups by Ziyi Wang, Fan Zhang, Shiji Ma, Hailong Wang, Shunyao Zhang, Xiaozhong Gao

“…Subsequently, the network model is trained to improve its solution capabilities using the policy gradient algorithm (REINFORCE). …”
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Study on the Speed Ratio Control of Fuzzy PID Control for EM- CVT based on PSO by Zhang Lanchun, Liu Sen, Wang Wei, Shen Hongsheng, Wang Shanfeng

“…The Fuzzy PID speed ratio controller model is set up,whose parameter factors are optimized by the PSO algorithm to realize the optimization of the speed ratio control system. …”
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Reliability Prediction for Computer Numerical Control Machine Servo Systems Based on an IPSO-Based RBF Neural Network by Zheng Jiang, GuangJian Wang, ZuGuang Huang, Ye He, RuiJuan Xue

“…A novel reliability prediction model based on radial basis function (RBF) neural network optimized by improved particle swarm optimization (IPSO) was proposed. …”
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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…Optimizing hyperparameters of five models using the Particle Swarm Optimization (PSO) algorithm. …”
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An Interior Point Method for L1/2-SVM and Application to Feature Selection in Classification by Lan Yao, Xiongji Zhang, Dong-Hui Li, Feng Zeng, Haowen Chen

“…By the use of the L1/2 regularization technique, we propose a new model L1/2-SVM. To solve this nonconvex and non-Lipschitz optimization problem, we first transform it into an equivalent quadratic constrained optimization model with linear objective function and then develop an interior point algorithm. …”
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Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

“…Specifically, in order to improve optimization efficiency, greedy bilateral smoothing is employed to model low rank backgrounds, resulting in a significant improvement in the efficiency of the detection algorithm. …”
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Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

“…Specifically, the Intelligent Voyage Optimization algorithm effectively tunes the model hyperparameters and the deployment of hybrid features contributes to the proposed model to detect attack patterns effectively. …”
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Research on the evaluation method of cooperative jamming effectiveness based on IPSO-ELM by A. Tianjian Yang, B. Xing Wang, C. Siyi Cheng, D. You Chen, E. Xi Zhang

“…This optimization aims to boost the model’s predictive precision. …”
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Advanced leukocyte classification using attention mechanisms and dual channel U-Net architecture by Gauri Kalnoor, Vijayalaxmi Kadrolli

“…The image quality is boosted in the preprocessing phase through noise reduction, contrast enhancement, and background removal, significantly improving clarity. Then, the Dung Beetle Optimization (DBO) algorithm enhanced with Levy flight optimization is implemented for effective image segmentation processes. …”
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