An improved ant colony optimization strategy for dual-objective high-speed train scheduling by Hui Zhao, Jiahuan Zhang, Haixing Li, Dong Li

“…Then, an improved ant colony optimization algorithm is proposed to solve the model. …”
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CFD-based aerodynamic optimization of the fairing for a high-speed elevator by Xiawei Shen, Aimin Wang, Wanbing Liu, Rongyang Wang

“…The cross-section of the fairing is parameterized by NURBS curves; then, the Latin experimental design method is used to generate test sample points, a mathematical model is formulated utilizing the response surface model approximation, and global optimization is conducted through the application of a multi-island genetic algorithm. …”
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A multi-strategy improved snake optimizer and its application to SVM parameter selection by Hong Lu, Hongxiang Zhan, Tinghua Wang

“…Nevertheless, SO has the shortcomings of weak population initialization, slow convergence speed in the early stage, and being easy to fall into local optimization. To address these problems, an improved snake optimizer algorithm (ISO) was proposed. …”
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Diverse solitons wave structures for coupled NLSEs in birefringent fibers with higher nonlinearities using the modified extended mapping algorithm by Karim K. Ahmed, Njah A. Alsahafi, Hamdy M. Ahmed, Salah Boulaaras, M. S. Osman

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Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
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Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…This paper presents a reinforcement learning-based approach to automate the tuning of a 6thorder combline bandpass filter, operating at 941 MHz, using a Q-learning algorithm. To reduce complexity, only two tuning screws are considered in the optimization. …”
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Research on improving the ranging accuracy of ships with stereo vision through Kalman filter optimization. by Zhongbo Peng, Jie Han, Liang Tong, Lumeng Wang, Dan Liu, Shijie Sun

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Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

“…The methodology results in a 38% reduction in total assembly errors, improving both process accuracy and efficiency. Specifically, the PSBFO algorithm reduced errors from an initial value of 50 to a final value of 5 across 20 iterations, with components such as the low-speed shaft and planetary gear system showing the most substantial reductions. …”
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Optimization method for educational resource recommendation combining LSTM and feature weighting by Meixia Yang

“…Finally, the bidirectional long short-term memory network algorithm is used for encoding iteration to minimize data omission and improve data interactivity, achieving accurate recommendation of educational resources. …”
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Load forecasting of microgrid based on an adaptive cuckoo search optimization improved neural network by Liping Fan, Pengju Yang

“…Finally, the weights and biases of the forecasting model were optimized by the improved cuckoo search algorithm. …”
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Detecting cyber attacks in vehicle networks using improved LSTM based optimization methodology by C. Jayasri, V. Balaji, C. M. Nalayini, S. Pradeep

“…Detection is executed through an Improved Long Short-Term Memory (ILSTM) model, whose parameters are optimized using the Crocodile Optimization Algorithm (COA), aiming to maximize classification accuracy. …”
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On the Use of an Improved Artificial Fish Swarm Algorithm-Backpropagation Neural Network for Predicting Dam Deformation Behavior by Bo Dai, Hao Gu, Yantao Zhu, Siyu Chen, E. Fernandez Rodriguez

“…The hybrid model’s preciseness is verified against the radial displacements of a pendulum in a concrete arch dam and simulations of four models: statistical model, BP-ANN optimized by genetic algorithm (GA), particle swarm optimization (PSO), and AFSA. …”
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Comparative analysis of FACT devices for optimal improvement of power quality in unbalanced distribution systems by Ahmed M. Elkholy, Dmitry I. Panfilov, Ahmed E. ELGebaly

“…To improve network asymmetry, an optimization analysis is carried out to ascertain how each proposed device will work. …”
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Angular Random Walk Improvement of Resonator Fiber Optic Gyro by Optimizing Modulation Frequency by Wei Gao, Zhuo Wang, Guochen Wang, Weiqi Miao

“…In order to make this method effective, we use the particle swarm optimization algorithm to optimize the multi-parameter involved in ARW. …”
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Improved Data Transmission Scheme of Network Coding Based on Access Point Optimization in VANET by Zhe Yang, Lingzhi Li, Wenqiang Yao, Kaisheng Xu, Dongxin Tang

“…So the AP deployment is one of the key issues to improve the communication performance of VANET. In this paper, an access point optimization method is proposed based on particle swarm optimization algorithm. …”
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Machine Learning-Assisted Optimization of Femtosecond Laser-Induced Superhydrophobic Microstructure Processing by Lifei Wang, Yucheng Gu, Xiaoqing Tian, Jun Wang, Yan Jia, Junjie Xu, Zhen Zhang, Shiying Liu, Shuo Liu

“…Furthermore, by utilizing this small sample dataset, various machine learning algorithms were employed to establish a prediction model for the contact angle, among which support vector regression demonstrated the optimal predictive accuracy. …”
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5G-Practical Byzantine Fault Tolerance: An Improved PBFT Consensus Algorithm for the 5G Network by Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

“…With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant consensus algorithm with three ways to improve PBFT. …”
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An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis by Yao Zhang, Xu Wang, Haohua Xiu, Wei Chen, Yongxin Ma, Guowu Wei, Lei Ren, Luquan Ren

“…Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. …”
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Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma by Bingxin Zhang, Dong Zheng, Shuxia Zhu, Xinyi Zhang, Quanqiang Wang, Zhili Lin, Ziwei Zheng, Shujuan Zhou, Zixing Chen, Sisi Zheng, Enqing Lan, Luning Cui, Hansen Ying, Yu Zhang, Xuanru Lin, Qiang Zhuang, Honglan Qian, Xudong Hu, Yan Zhuang, Qianying Zhang, Zhouxiang Jin, Songfu Jiang, Yongyong Ma, Yongyong Ma, Yongyong Ma

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Impact of Coordinated Electric Ferry Charging on Distribution Network Using Metaheuristic Optimization by Rajib Baran Roy, Sanath Alahakoon, Piet Janse Van Rensburg

“…Using DIgSILENT PowerFactory integrated with MATLAB Simulink and a Python-based control system, four proposed ferry terminals equipped with BESSs (Battery Energy Storage Systems) are simulated. A dynamic model of BESS operation is optimized using a balanced hybrid metaheuristic algorithm combining GA-PSO-BFO (Genetic Algorithm-Particle Swarm Optimization-Bacterial Foraging Optimization). …”
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