IMPROVEMENT ALGORITHM OF TIME-VARYING MESHING STIFFNESS OF HELICAL GEAR AND ANALYSIS OF INFLUENCING FACTORS by WU LuJi, YANG ShiHao, FENG Wei, YANG LinJie

“…This method considered the parameter equation of the transition curve of the real tooth root, corrected the integral interval of the involute tooth profile, and compared with the finite element method to verify the validity of the algorithm and reduce the calculation error of the time-varying mesh stiffness. …”
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Research on 3D Path Optimization for an Inspection Micro-Robot in Oil-Immersed Transformers Based on a Hybrid Algorithm by Junji Feng, Xinghua Liu, Hongxin Ji, Chun He, Liqing Liu

“…Simulation results demonstrate that the hybrid algorithm achieves a 52.6% reduction in path length compared to the unoptimized A* algorithm, with the A*-ACO combination exhibiting exceptional stability. …”
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Ship Formation and Route Optimization Design Based on Improved PSO and D-P Algorithm by Peilong Xu, Dan Lan, Haolin Yang, Shengtian Zhang, Hyeonseok Kim, Incheol Shin

“…The particle swarm algorithm introduces dynamic adaptive parameter adjustment and the cross mutation strategy of genetic algorithm, while the Douglas-Peucker algorithm integrates density-based noise application spatial clustering algorithm to improve model performance. …”
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Research on site selection and capacity determination problem based on improved particle swarm algorithm by Xiaotong Mi, Qinyang Liu, Bo Geng, Yong Zhu

“…The optimal solution of the improved PSO algorithm is combined with the initial value of the ant colony algorithm and deployed in the IEEE33 node system for site selection. …”
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ISAR Autofocus Imaging Algorithm for Maneuvering Targets Based on Phase Retrieval and Keystone Transform by Hongyin Shi, Ting Yang, Yue Liu, Jingjing Si

“…In the case of the high-speed maneuvering target with a small value of rotation, the phase retrieval algorithm can be applied to compensate for the translational motion to form an autofocusing image. …”
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Improved gray wolf harris hawk algorithm based feature selection for sentiment analysis by Tamara Amjad Al-Qablan, Mohd Halim Mohd Noor, Mohammed Azmi Al-Betar, Ahamad Tajudin Khader

“…Experimental results show that the Aβ-BGWHHO algorithm outperforms other algorithms regarding accuracy, feature reduction, and fitness value. …”
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Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms by Alejandro Kevin Méndez Castillo, Elizabeth Contreras López, Jesús Guadalupe Pérez Flores, Laura García Curiel, Emmanuel Pérez Escalante, Karla Soto Vega, Carlos Ángel-Jijón, Alicia Cervantes Elizarrarás

“… This research aimed to automate the fitting of kinetic models using genetic algorithms (GAs) to optimize the estimation of kinetic parameters—the reaction rate constant (k) and the initial value of total titratable acidity (TTA, C₀)—and enhance predictive accuracy. …”
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A distributed CRN resource allocation algorithm based on CBR and cooperative Q-learning by Lin XU, Zhijin ZHAO

“…In order to solve the problem of channel and power allocation in distributed cognitive radio networks (CRN),a case-based reasoning (CBR) and cooperative Q-learning algorithm was proposed.In order to optimize the Q initialization of Q-learning algorithm,the current problem and the historical case were matched according to the similarity function,the Q value of the matching case was extracted and normalized as the initial value.Cooperative Q-learning was based on the total reward value,and each agent integrates the Q values of other agents with higher reward values with different weights to gain learning experience to reduce unnecessary exploration.Simulations show that the proposed algorithm can improve the energy efficiency of the cognitive system’s channel and power allocation,and accelerate the convergence speed of the system.…”
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A distributed CRN resource allocation algorithm based on CBR and cooperative Q-learning by Lin XU, Zhijin ZHAO

“…In order to solve the problem of channel and power allocation in distributed cognitive radio networks (CRN),a case-based reasoning (CBR) and cooperative Q-learning algorithm was proposed.In order to optimize the Q initialization of Q-learning algorithm,the current problem and the historical case were matched according to the similarity function,the Q value of the matching case was extracted and normalized as the initial value.Cooperative Q-learning was based on the total reward value,and each agent integrates the Q values of other agents with higher reward values with different weights to gain learning experience to reduce unnecessary exploration.Simulations show that the proposed algorithm can improve the energy efficiency of the cognitive system’s channel and power allocation,and accelerate the convergence speed of the system.…”
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An Algorithm for Restoring a Function from Different Functionals for Predicting Rare Events in the Economy by Yu. A. Korablev

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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…Both these metrics surpass those of existing mainstream multi-task perception algorithms with comparable parameter scales. Furthermore, the lane line segmentation accuracy, measured by IoU, reached a sub-optimal value of 27.2%. …”
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Research on distributed cooperative algorithm based on signal-to-noise ratio coefficient with double thresholds by Li Zhanxiong, Liu Liping, Fang Liang, Lv Jiafeng, Wang Ci

“…The threshold value of the algorithm is adaptively adjusted according to the signal-to-noise ratio coefficient. …”
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A node influence ranking algorithm combining k-shell iteration and node degree. by Yating Ji, Lequn Liu, Shujia Li, Pu Lu, Qimei Tang

“…To address this issue, we propose a node influence ranking algorithm that integrates K-shell iteration, node degree, and neighbor information, considering both global network position and local topology. …”
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Application of machine learning algorithm for prediction of abortion among reproductive age women in Ethiopia by Angwach Abrham Asnake, Alemayehu Kasu Gebrehana, Hiwot Altaye Asebe, Beminate Lemma Seifu, Bezawit Melak Fente, Meklit Melaku Bezie, Mamaru Melkam, Sintayehu Simie Tsega, Yohannes Mekuria Negussie, Zufan Alamrie Asmare

“…Additionally, giving birth for the first time before the age of 18 ranked third, with a mean SHAP value of + 0.052. This study underscores the value of integrating machine learning into public health research and practice. …”
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Application effect of short-term traffic flow prediction method based on CNNBLSTM algorithm. by Guozhu Sui, Meixia Song, Ke Bian, Mingzhen Zhang, Xiaogang Zhang, Yiru Wang

“…To address this problem, this study proposes a short-term traffic flow prediction method based on an improved convolutional neural network and a bidirectional long short-term memory algorithm. The method firstly identifies, repairs and decomposes the abnormal traffic flow data by smoothing the estimation threshold and adaptive noise integration empirical modal decomposition method to improve the data quality and stability. …”
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Predictive PID Control for Automated Guided Vehicles Using Genetic Algorithm and Machine Learning by Kinza Nazir, Yong-Woon Kim, Yung-Cheol Byun

“…The integration of automated guided vehicles (AGVs) in industrial automation demands precise and adaptive control systems for efficient path tracking. …”
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Personalized Recommendation Algorithm for Cultural and Creative Products Based on Fuzzy Decision Support System by Lin Shi, Xiaoqing Yang

“…Hence, this study proposes a fuzzy context-aware neural recommendation algorithm (F-CANRA) to analyze consumers’ purchase behaviors regarding cultural and creative products (CCPs). …”
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Fitting Penalized Estimator for Sparse Covariance Matrix with Left-Censored Data by the EM Algorithm by Shanyi Lin, Qian-Zhen Zheng, Laixu Shang, Ping-Feng Xu, Man-Lai Tang

“…However, the fitting of these penalized estimators poses challenges due to the observed log-likelihood involving high-dimensional integration over the censored variables. To address this issue, we treat censored data as a special case of incomplete data and employ the Expectation Maximization algorithm combined with the coordinate descent algorithm to efficiently fit the two penalized estimators. …”
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Efficiently Automating Covering Array Generation: A Model Checking and Metaheuristic Algorithm Approach by Sajad Esfandyari, Davar Giveki, Amir Rastegarnia, Ali Farzamnia, Hua Zheng

“…The GROOVE model checker extracts parameters and their values, which are then optimized by the BBO and GA algorithms to generate a minimal and effective test suite. …”
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Fast and Accurate Numerical Integration of the Langevin Equation with Multiplicative Gaussian White Noise by Mykhaylo Evstigneev, Deniz Kacmazer

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