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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Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops by Xin Yang, Xiaoying Yang, Jinhao Du

“…Furthermore, an improved crowding distance calculation enhances the algorithm’s performance in multi-objective optimization by improving solution distribution. …”
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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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Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm by Xu Chen, Changhai Ma, Quanli Dou, Shuzhan Bai, Ke Sun, Zhenguo Li

“…In this study, test data were obtained from an engine test stand and a Support Vector Machine (SVM) was developed using the test data to predict NOx conversion efficiency and NH₃ slip. The SVM model was optimized using the Crested Porcupine Optimizer (CPO) to improve its prediction accuracy and was made to replace the mathematical model to save computational time. …”
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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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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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Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

“…The main motivation for the development of FCMA has been to significantly reduce the solving time of the resource allocation problem compared to a previous state-of-the-art optimal Integer Linear Programming (ILP) model. In addition, FCMA addresses secondary objectives to improve fault tolerance and reduce container and virtual machine recycling costs, load-balancing overloads and container interference. …”
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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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MQHOA algorithm with energy level stabilizing process by Peng WANG, Yan HUANG

“…An improved multi-scale quantum harmonic oscillator algorithm (MQHOA) with energy level stabilizing process was proposed analogizing to quantum harmonic oscillator's wave function. …”
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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Research on optimal selection of runoff prediction models based on coupled machine learning methods by Xing Wei, Mengen Chen, Yulin Zhou, Jianhua Zou, Libo Ran, Ruibo Shi

“…Employing a “decomposition-reconstruction” strategy combined with robust optimization algorithms enhances the performance of machine learning prediction models, thereby significantly improving the runoff prediction capabilities in watershed hydrological models.…”
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Optimization of fuzzy bottleneck cost transportation models in the decision framework of congruence modulo technique by Kapil Kumar, Nandini, Tarun Kumar, Kailash Dhanuk, Anirudh Kumar Bhargava, M.K. Sharma

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Variance Reduction Optimization Algorithm Based on Random Sampling by GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang

“…To address the above challenge, a variance reduction optimization algorithm, DM-SRG (double mini-batch stochastic recursive gradient), based on mini-batch random sampling is proposed and applied to solving convex and non-convex optimization problems. …”
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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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Sustainable soil organic carbon prediction using machine learning and the ninja optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy

“…To address these challenges, we propose a novel integration of the Ninja Optimization Algorithm (NiOA) for simultaneous feature selection and hyperparameter optimization, aimed at enhancing both predictive accuracy and computational efficiency. …”
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Improved active vibration control of a cantilever beam using MFC actuators with Hammerstein model-based hysteresis modeling and VSS-FxLMS control algorithm by Hafiz Muhammad Umar, Lei Zhang, Ruichen Yu, Zhiyuan Gao

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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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Research on Wafer CMP Temperature Online Detection Compensation Algorithm Based on GA-BP Improved Neural Network by Binjie Li, Kuan Shen, Zhilong Song, Binghai Lyu, Wenhong Zhao

“…The improved genetic algorithm-optimized backpropagation (GA-BP) neural network model incorporates a dynamic nonlinear probability adjustment mechanism and a fitness calibration mechanism. …”
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Presenting a Prediction Model for CEO Compensation Sensitivity using Meta-heuristic Algorithms (Genetics and Particle Swarm) by Saeed Khaljastani, Habib Piri, Reza Sotoudeh

“…Given these points, the aim of this research is to provide a model for predicting the sensitivity of CEO compensation using meta-heuristic algorithms, specifically genetic algorithms and particle swarm optimization. …”
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