Federated learning optimization algorithm based on incentive mechanism by Youliang TIAN, Shihong WU, Ta LI, Lindong WANG, Hua ZHOU

“…Federated learning optimization algorithm based on incentive mechanism was proposed to address the issues of multiple iterations, long training time and low efficiency in the training process of federated learning.Firstly, the reputation value related to time and model loss was designed.Based on the reputation value, an incentive mechanism was designed to encourage clients with high-quality data to join the training.Secondly, the auction mechanism was designed based on the auction theory.By auctioning local training tasks to the fog node, the client entrusted the high-performance fog node to train local data, so as to improve the efficiency of local training and solve the problem of performance imbalance between clients.Finally, the global gradient aggregation strategy was designed to increase the weight of high-precision local gradient in the global gradient and eliminate malicious clients, so as to reduce the number of model training.…”
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Federated learning optimization algorithm based on incentive mechanism by Youliang TIAN, Shihong WU, Ta LI, Lindong WANG, Hua ZHOU

“…Federated learning optimization algorithm based on incentive mechanism was proposed to address the issues of multiple iterations, long training time and low efficiency in the training process of federated learning.Firstly, the reputation value related to time and model loss was designed.Based on the reputation value, an incentive mechanism was designed to encourage clients with high-quality data to join the training.Secondly, the auction mechanism was designed based on the auction theory.By auctioning local training tasks to the fog node, the client entrusted the high-performance fog node to train local data, so as to improve the efficiency of local training and solve the problem of performance imbalance between clients.Finally, the global gradient aggregation strategy was designed to increase the weight of high-precision local gradient in the global gradient and eliminate malicious clients, so as to reduce the number of model training.…”
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Multi-strategy improved runge kutta optimizer and its promise to estimate the model parameters of solar photovoltaic modules by Serdar Ekinci, Rizk M. Rizk-Allah, Davut Izci, Emre Çelik

“…In our endeavor, we introduce a multi-strategy improvement approach for the Runge Kutta (RUN) optimizer, a cutting-edge tool used for tackling this critical task in both single-diode and double-diode PV unit models. …”
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The PSO-IFAH optimization algorithm for transient electromagnetic inversion. by Zhengyu Xu, Guofeng Zhao, Xian Liao, Nengyi Fu

“…And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. …”
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The application of ICPA optimization algorithm in multi-objective optimization structural design of prefabricated buildings by Chao Li

“…Finally, a novel structural design optimization model was proposed. These experiments confirmed that the improved algorithm had the least 160 iterations and 17 optimal solutions, which was an increase of 15 compared to traditional aphid algorithms. …”
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Parametric Optimization of Train Brake Pad Using Reverse Engineering with Digital Photogrammetry 3D Modeling Method by P Paryanto, Muhammad Faizin, R Rusnaldy

“…This was followed by processing 2D images using Agisoft Metashape 2.2.1 software and Artificial Intelligence (AI) algorithms to create a precise 3D model. Subsequently, assessment was performed using feasibility in terms of cost, time, and accuracy. …”
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Mixed Production Line Optimization of Industrialized Building Based on Ant Colony Optimization Algorithm by Xiaobo Chen, Fangfang Yu, Hengyu Zhou, Zhengdao Li, Kuo-Jui Wu, Xikun Qian

“…In order to optimize the large random orders in the prefabricated components production process, this research proposes a model to minimize variance of the production capacity utilization of prefabricated components in the production cycle, and the ant colony optimization algorithm is introduced to solve the mixed production line sequencing optimization problem. …”
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AI-Based Classification Model for Low-Energy Buildings: Promoting Sustainable Economic Development of Smart Cities With Spherical Fuzzy Decision Algorithm by Lin Yang

“…AI-based classification models for low-energy buildings are essential in promoting the economic development of smart cities by optimizing energy use, reducing operational costs, and enhancing overall efficiency. …”
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Improving the performance of a two-phase ejector using genetic algorithm based on secondary fluid entrainment rate by M. Moghadasi, M. Moraveji, O. Alizadeh

“…Using a multi-objective genetic algorithm, the optimal values for each parameter are obtained. …”
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Research of the Parameter Comprehensive Optimization of Excavator Working Device based on the Hybrid Optimization Algorithm by Zhang Xian, Liu Baixi, Qu Tao

“…The efficiency and accuracy of the solution is improved for the advantages of two algorithms are effectively combined and local optimal solution is avoided. …”
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A new adaptive grey prediction model and its application by Jianming Jiang, Ming Zhang, Zhongyong Huang

“…Specifically, the Marine Predators Optimization algorithm is introduced to facilitate the model’s solution process. …”
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A Hybrid Algorithm with a Data Augmentation Method to Enhance the Performance of the Zero-Inflated Bernoulli Model by Chih-Jen Su, I-Fei Chen, Tzong-Ru Tsai, Yuhlong Lio

“…This zero-inflated structure significantly contributes to data imbalance. To improve the ZIBer model’s ability to accurately identify minority classes, we explore the use of momentum and Nesterov’s gradient descent methods, particle swarm optimization, and a novel hybrid algorithm combining particle swarm optimization with Nesterov’s accelerated gradient techniques. …”
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Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

“…Separate optimization of weighting processing for each frequency channel can significantly improve the average efficiency characteristics of a multichannel Doppler filter and eliminate all the shortcomings of the classical and modified FFT algorithms when processing non-equidistant pulse sequences. …”
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Optimization of Sorghum Spike Recognition Algorithm and Yield Estimation by Mengyao Han, Jian Gao, Cuiqing Wu, Qingliang Cui, Xiangyang Yuan, Shujin Qiu

“…By integrating the GOLD module’s dual-branch multi-scale feature fusion and the LSKA attention mechanism, a lightweight detection model is developed. The improved DeepSort algorithm enhances tracking robustness in occlusion scenarios by optimizing the confidence threshold filtering (0.46), frame-skipping count, and cascading matching strategy (n = 3, max_age = 40). …”
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Reliability growth model of quantum direct current electricity meter software based on optimization network by TIAN Teng, QIU Rujia, ZHAO Long, GENG Jiaqi, WANG Enhui, SUN Yu

“…This improves the modeling efficiency by 18 times and significantly improves global optimization ability of the back propagation neural network. …”
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Research on Interval Probability Prediction and Optimization of Vegetation Productivity in Hetao Irrigation District Based on Improved TCLA Model by Jie Ren, Delong Tian, Hexiang Zheng, Guoshuai Wang, Zekun Li

“…Experimental data indicate that the TCLA model improves prediction accuracy by 10.57–26.47% compared to conventional models (Long Short-Term Memory (LSTM), Transformer). …”
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Modeling Analysis and Simulation Verification for Drive Tooth Stress of Rubber Track Wheel by Zihan Zhao, Xihui Mu, Fengpo Du, Jianhua Guo

“…Firstly，based on structure parameters and transmission principle，the drive tooth profile equation is established and determining mapping parameters by the improved Powell algorithm. The optimization results show that the accuracy of the mapping tooth profile obtained by this method is 0.12%，which effectively improves the mapping accuracy. …”
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STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK by LI YongHua, CHEN Peng, TIAN ZongRui, CHEN ZhiHao

“…Aiming at the problems that traditional BP neural network surrogate model had deficiency of fitting accuracy and computational efficiency, the Mind Evolutionary Algorithm was used to optimize BP neural network and an improved BP neural network surrogate model reliability calculation method was proposed. …”
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SAHAANN: A NOVEL EVOLUTIONARY ARTIFICIAL NEURAL NETWORK FOR IMPROVED FINANCIAL TIME SERIES FORECASTING by Abdul Khadeer, Vanaparthi Kiranmai, B. Suvarnamukhi, Ayaz Mohiuddin, Balika Mahesh, P M Suresh, J Arthy, Sasikumar A N, Sudersan Behera, Mohd Ayaz Uddin

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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

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