High-efficiency MPPT Using ZVS quasi-resonant converter and PSO algorithm: Simulation and PIL validation by Souhail Barakat, Abdelouahed Mesbahi, Badr N’hili, Ayoub Nouaiti, Mohcine Abouyaakoub

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Analytical and Geometric Foundations and Modern Applications of Kinetic Equations and Optimal Transport by Cécile Barbachoux, Joseph Kouneiher

“…By bridging entropy dissipation, optimal transport, and geometric analysis, our work offers a new perspective on stability, convergence, and structure in high-dimensional kinetic models and applications.…”
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Inventory Optimization of Fresh Agricultural Products Supply Chain Based on Agricultural Superdocking by Lixin Shen, Fucheng Li, Congcong Li, Yumin Wang, Xueqi Qian, Tao Feng, Cong Wang

“…An improved genetic algorithm is developed to solve the nonlinear optimization problem. …”
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Structural design and optimization of egg carrier for dynamic egg slit detection platforms. by Ronghua Meng, Yuxiang Tian, Siwei Huang

“…On the basis of stable egg carrying, a carrying motion mathematical model is established, and the genetic algorithm (GA) is chosen to optimize the structural parameters. …”
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Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis by Yuxing Liu, Jintao Chen, Daifeng Yang, Chenming Liu, Chunhui Tang, Shanshan Cai, Yingxuan Huang

“…Utilizing transcriptomic and gene expression data from TCGA and GEO databases, 72 immune-related lncRNAs were identified through weighted gene co-expression network analysis (WGCNA) and ImmuLncRNA algorithms. The model was further optimized using 101 combinations of 10 machine learning approaches, ultimately constructing an immune-related lncRNA signature(IRLS) scoring system comprising nine key lncRNAs. …”
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Adaptive resource optimization mechanism for blockchain sharding in digital twin edge network by Li JIANG, Shengli XIE, Hui TIAN

“…To address the security and privacy issues for data sharing in digital twin edge networks, a new distributed and secure data sharing mechanism was developed by leveraging blockchain sharding.Considering dynamic and time varying features in digital twin edge networks and mapping errors of physic networks, an adaptive resource allocation model was formulated which jointly optimized cluster head selection, local base station (BS) consensus access selection, spectrum and computation consensus resources allocation, in order to maximize transactional throughput for the blockchain sharding.Moreover, a digital twin edge networks empowered two-layered proximal policy optimization (PPO) algorithm was designed to obtain the optimal solutions.Numerical results illustrate that the proposed algorithm can effectively improve the transactional throughput for the blockchain sharding.Meanwhile, it can well adapt to the mapping errors.…”
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Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach by Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu

“…Predictive models were constructed using eight machine learning algorithms and two ensemble algorithms, with the optimal model identified through AUROC. …”
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Understanding visitor flow and behaviour in developing tourism-service-oriented villages by space syntax methodologies: a case study of Tabian Rural Section of Qingshan Village, Ha... by Shuqin Wang, Yan Huang, Tianjie Li

“…This study innovatively combines space syntax models for extended application in the research of rural BEs, providing guidance for optimizing strategies to improve spatial configuration in homogeneous villages.…”
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Random Forest-Based Prediction of the Optimal Solid Ink Density in Offset Lithography by Laihu Peng, Hao Fan, Yubao Qi, Jianqiang Li

“…To improve the efficiency of determining the optimal solid ink density, the Random Forest algorithm was applied for the first time to the prediction task of solid ink density in offset printing. …”
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Design and Multiobjective Optimization of Magnetorheological Damper considering the Consistency of Magnetic Flux Density by Zhizhen Dong, Zhimin Feng, Yuehua Chen, Kefan Yu, Gang Zhang

“…Then, the multiobjective optimization function and the working flow of optimal design are presented by combining the parallel-plate model of the MR damper with the function posed before. …”
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Research on optimization of vector control of an asynchronous motor using the analytical control system by A. N. Tsvetkov, Ngok Shi Doan, D. A. Yaroslavsky

“…The control algorithm based on determining the optimal value of the magnetic flux in the coordinates of the d - q axis to achieve low power losses, taking into account losses in the iron core and low magnetic saturations, helps to improve the efficiency of inverter control.RESULTS. …”
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Inversion of Crop Water Content Using Multispectral Data and Machine Learning Algorithms in the North China Plain by Zhenghao Zhang, Gensheng Dou, Xin Zhao, Yang Gao, Saisai Liu, Anzhen Qin

“…Future studies could consider expanding sample sizes and improving data collection methods to overcome these limitations.…”
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Parking Demand Prediction Method of Urban Commercial-Office Complex Buildings Based on the MRA-BAS-BP Algorithm by Xiang Tang, Jianxiao Ma, Shun Zhou, Tianci Shan

“…In this paper, a two-level and ten-category index system is established and then mixed with the BP algorithm through the MRA model to improve the overall robustness and accuracy of the algorithm. …”
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Clean energy supply chain optimization: Steady-state natural gas transportation by Zhongfu Liu, Shuiying Xu, Shihao Zhao, Yuewen Li, Meiling Zhou, Shuosen Li, Fei Meng

“…Experimental results show that the proposed model and algorithm significantly improve the efficiency of the clean energy supply chain, providing theoretical support for the low-carbon and economic aspects of natural gas transportation.…”
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Optimal strategy selection method for moving target defense based on signaling game by Lyu JIANG, Hengwei ZHANG, Jindong WANG

“…To solve the problem of the optimal strategy selection for moving target defense,the defense strategy was defined formally,the defense principle from the perspective of attack surface shifting and exploration surface enlarging was taken into account.Then,network attack-defense behaviors were analyzed from the sight of dynamic confrontation and bounded information.According to the analysis of attack-defense game types and confrontation process,the moving target defense model based on signaling game was constructed.Meanwhile,the method to quantify strategies was improved and the solution of perfect Bayesian equilibrium was proposed.Furthermore,the optimal defense strategy selection algorithm was designed by the equilibrium analysis.Finally,the simulation demonstrates the effectiveness and feasibility of the proposed optimal strategy and selection method.…”
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Optimal Coordination of Last Trains for Maximum Transfer Accessibility with Heterogeneous Walking Time by Yao Chen, Baohua Mao, Yun Bai, Tin Kin Ho, Zhujun Li

“…A discrete approximation method is proposed to reformulate the nonlinear model. The embedded Branch & Cut algorithm of CPLEX is applied to solve the models. …”
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Accuracy–Efficiency Trade-Off: Optimizing YOLOv8 for Structural Crack Detection by Jiahui Zhang, Zoia Vladimirovna Beliaeva, Yue Huang

“…To address the accuracy–efficiency trade-off faced by deep learning models in structural crack detection, this paper proposes an optimized version of the YOLOv8 model. …”
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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…To further optimize model performance, the pelican optimization algorithm (POA) is utilized for hyperparameter tuning to ensure that the optimum hyperparameters are chosen for enhanced accuracy. …”
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Cancer Diagnosis Optimization With a Combination of Flexible THz Antennas and Machine Learning by M. Senthil Pandian, S. Deepa Nivethika, J. Idhikash, Vamsee N. Yashwanth, Aishwarya Shaji, Prabhakaran Paulraj

“…The optimization of the decision was done using the combination of K‐means and logistic regression algorithm to determine 95.06% efficiency.…”
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Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

“…It is assumed that the improvement of ML-based models and their introduction into clinical practice will help support medical decision-making, increase the effectiveness of treatment and optimize health care costs.…”
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