Target Detection Label Assignment Method Based on Global Information by ZHANG Pei-pei, LU Zhen-yu

“…With the development of deep learning framework, new object detection algorithms have also been proposed, such as first-stage and two-stage detection models, which have improved the detection speed and solved the problem of object detection at different scales, but they have not yet been well solved for overlapping, occlusion and other issues. …”
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Using machine learning algorithms to predict colorectal polyps by Xingjian Xiao, Shiyou Liu, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Xianglong Xu

“…The optimal model was used to identify predictors of colorectal polyps. …”
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Predictive modeling of hydrogen production and methane conversion from biomass-derived methane using machine learning and optimisation techniques by Adegboyega Bolu Ehinmowo, Bright Ikechukwu Nwaneri, Joseph Oluwatobi Olaide

“…The study hence established the great opportunity of integration of machine learning models with optimisation techniques in attempts to improve the prediction of hydrogen yield and methane conversion in processes for hydrogen production.…”
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Provident garbage collection algorithm for SSD storage system by Xuezhen TU, Zhenjiang Huang, Zhengguang CHEN

“…A predictive based proactive garbage collection algorithm was proposed.Firstly,the data was separated according to different heat factors,then the upper and lower predictions were performed on the number of different types of page allocation requests (PAR) that would be reached in the future.While satisfying the page allocation request lower prediction,the PAR upper prediction requirement was maximally satisfied,the WA problem was optimized,and invalid effective data migration was reduced,thereby maximizing the garbage collection utility.A mathematical model was defined for this problem,and an algorithm for obtaining the approximate optimal solution was given.The applicable scenario of the model was analyzed.The practical results show that the algorithm can obtain the maximum benefit and can significantly improve the performance of SSD and reduce the cost.…”
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Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome by Weirong Xue, Bing Xu, Hui Wang, Xiaoxiao Zhu, Jiajia Qin, Guangshuang Zhou, Peilin Yu, Shengli Li, Yingliang Jin

“…Hyperparameters for each model were optimized using the particle swarm optimization (PSO) algorithm on the validation set. …”
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Modified tree-based selection in hierarchical mixed-effect models with trees: A simulation study and real-data application by Asrirawan, Khairil Anwar Notodiputro, Budi Susetyo, Sachnaz Desta Oktarina

“…However, this algorithm relies on a greedy approach, making the trees prone to overfitting, biased in split selection, and often far from the optimal solution, ultimately affecting model performance. …”
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Design of Chinese Corpus Based on Semantic Mining Algorithm by Di Wu

“…In order to improve the practical effect of the Chinese corpus, this paper combines the semantic mining algorithm to design the Chinese corpus, proposes an ontology adaptive algorithm based on content learning, and conducts in-depth research on the model of the algorithm. …”
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Size optimization method of the Watt-II six-bar mechanism based on particle swarm optimization by H. Ye, H. Ye, Z. Niu, Z. Niu, D. Han, D. Han, X. Su, X. Su, W. Chen, W. Chen, G. Tu, G. Tu, T. Zhu, T. Zhu

“…<p>Aiming at the difficult problem of comprehensive scale design of the six-bar mechanism in engineering practice, kinematic and dynamic analysis and modeling of the Watt-II six-bar mechanism were carried out and combined with the particle swarm optimization (PSO) algorithm, the size optimization model of the Watt-II six-bar mechanism was established, and the size optimization of the Watt-II six-bar mechanism was completed. …”
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Optimizing Euclidean Distance Computation by Rustam Mussabayev

“…The Euclidean distance, being a computational bottleneck in large-scale optimization problems, requires efficient computation techniques to improve the performance of various distance-dependent algorithms. …”
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A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed-Loop Supply Chain by Hao Guo, Congdong Li, Ying Zhang, Chunnan Zhang, Yu Wang

“…Second, we develop a novel heuristic approach that incorporates simulated annealing into adaptive genetic algorithm to solve the model efficiently. Last, numerical analysis is presented to validate our solution approach, and it also provides meaningful managerial insight into how to improve the closed-loop supply chain under study.…”
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Future Smart Grids Control and Optimization: A Reinforcement Learning Tool for Optimal Operation Planning by Federico Rossi, Giancarlo Storti Gajani, Samuele Grillo, Giambattista Gruosso

“…A key insight is the use of historical real-world data to train the model, enabling its application in real-time scenarios. …”
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Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders. by Zuhair Alaas, Ghareeb Moustafa, Hany Mansour

“…The PO is a novel bio-inspired optimization algorithm that draws inspiration from pelicans' intelligence and behavior which incorporates unique methods for exploration and exploitation, improving its effectiveness in various optimization challenges. …”
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Construction and SHAP interpretability analysis of a risk prediction model for feeding intolerance in preterm newborns based on machine learning by Hui Xu, Xingwang Peng, Ziyu Peng, Rui Wang, Rui Zhou, Lianguo Fu

“…First, dual feature selection was conducted to identify important feature variables for model construction. Second, ML models were constructed based on the logistic regression (LR), decision tree (DT), support vector machine (SVM) and eXtreme Gradient Boosting (XGBoost) algorithms, after which random sampling and tenfold cross-validation were separately used to evaluate and compare these models and identify the optimal model. …”
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A Multi-Objective Particle Swarm Optimization Approach for Optimizing K-Means Clustering Centroids by Aina Latifa Riyana Putri, Joko Riyono, Christina Eni Pujiastuti, Supriyadi

“…This study evaluates the performance of the standard K-Means algorithm and proposes a Multiobjective Particle Swarm Optimization K-Means (MOPSO+K-Means) approach to improve clustering accuracy. …”
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A New Support Vector Regression Model for Equipment Health Diagnosis with Small Sample Data Missing and Its Application by Qinming Liu, Wenyi Liu, Jiajian Mei, Guojin Si, Tangbin Xia, Jiarui Quan

“…This paper proposes a novel small sample data missing filling method based on support vector regression (SVR) and genetic algorithm (GA) to improve equipment health diagnosis effect. …”
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Design, modeling and manufacture error identification of a new 6-degree-of-freedom (6-DOF) compliant parallel manipulator by H. Li, W. Chen, L. Yi, C. Leng, H. Wu

“…The Levenberg–Marquardt optimization algorithm is utilized to solve the identification model, with the results verified through finite-element analysis. …”
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A Bat Algorithm with Mutation for UCAV Path Planning by Gaige Wang, Lihong Guo, Hong Duan, Luo Liu, Heqi Wang

“…Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. …”
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Research on the Object Detection Algorithm Based on Fisheye Image by GAO Qun, ZHU Jun, WANG Qianqian, CAO Jie, XU Chao

“…It uses the feature pyramid structure to detect multi-scale objects, and combines the rotation and distortion characteristics of the fisheye to optimize the algorithm and directly detects the objects from the original fisheye image. …”
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A PSO-XGBoost Model for Predicting the Compressive Strength of Cement–Soil Mixing Pile Considering Field Environment Simulation by Jiagui Xiong, Yangqing Gong, Xianghua Liu, Yan Li, Liangjie Chen, Cheng Liao, Chaochao Zhang

“…Utilizing data mining on 84 sets of experimental data with various preparation parameter combinations, a prediction model for the as-formed strength of CSM Pile was developed based on the Particle Swarm Optimization-Extreme Gradient Boosting (PSO-XGBoost) algorithm. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Subsequently, the refined data undergoes feature selection employing an improved pigeon-inspired optimizer (PIO) algorithm. …”
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