Research on shale TOC prediction method based on improved BP neural network by Chaorong Wu, Kaixing Huang, Zhengtao Sun, Yizhen Li, Yong Li, Yuexiang Hao, Zhengxing Sun, Ziqi Wang

“…This paper studies a method for predicting shale TOC content using a BP neural network optimized by an improved cuckoo search algorithm. First, for the Longmaxi Formation shale, through logging sensitivity analysis, seven logging parameters sensitive to TOC content were determined: DEN, AC, RT, U, K, GR, and CNL. …”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…This paper proposes a YOLO-SRSA-based anomaly detection algorithm. For data enhancement, geometric and color transformations and rain-fog simulations are applied to preprocess the dataset, improving the model’s robustness in outdoor complex weather. …”
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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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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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An SVDD-based post-processing approach for vibration risk assessment of the hydro-turbine-generator in a large hydropower station by Jinliang Zhang, Fengwei Yang, Chao Liang, Yuansheng Zhang, Yongchang Li

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A state evaluation and fault diagnosis strategy for substation relay protection system integrating multiple intelligent algorithms by Jiajun Wang, Shiyi Jing, Yu Yao, Kunlun Wang, Bo Li

“…This study introduces a new diagnostic framework that combines improved particle swarm optimization, K‐means clustering algorithms, support vector machine (SVM), and learning vector quantization neural networks to provide a comprehensive fault diagnosis and prediction model for relay protection systems. …”
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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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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

“…To address these issues, a mixed-integer nonlinear optimization model is developed, and by linearizing the nonlinear equations, a sequential linear programming algorithm is proposed, iteratively updating the hydraulic parameters. …”
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Point Data Registration With the Multi-Object, Cardinalized Optimal Linear Assignment Metric by Pablo A. Barrios, Vicente Guzman, Martin D. Adams, Claudio A. Perez

“…The Iterative Closest Point (ICP) algorithm and its variants were initially used to solve such problems and since then, various global methods have been proposed to improve registration when data outliers exist. …”
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INNOVATIVE MECHANISMS FOR IMPLEMENTING STATE ECONOMIC POLICY FOR POST-WAR RECONSTRUCTION OF UKRAINE: QUANTUM TRANSFORMATIONS AS A DRIVER OF DEVELOPMENT by Oleksiy Shkuratov, Liudmila Antonova, Roman Dzyuba

“…The quantum transformation of Ukraine's economy in the conditions of post-war recovery can become an important component of the state investment policy, which will stimulate innovative development and increase the country's competitiveness in the international arena. …”
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Impact of Network Configuration on Hydraulic Constraints and Cost in the Optimization of Water Distribution Networks by Mojtaba Nedaei

“…Further, a new approach based on the Coral Reef Algorithm (CRA) is developed and implemented to improve the technical and economic viability of the designed WDNs. …”
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Weighted Filter Bank and Regularization Common Spatial Pattern-Based Decoding Algorithm for Brain-Computer Interfaces by Jincai Ye, Jiajie Zhu, Shoulin Huang

“…The algorithm divides the signal into multiple frequency bands, adaptively assigns subject weights based on the mutual information maximization criterion, and optimizes the covariance matrix with a regularization strategy, significantly improving the robustness of feature extraction. …”
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Reconstruction of porous media pore structure and simulation effect analysis of multi-index based on SNESIM algorithm by Qing Xie, Jiaqi Gao, Xiaochuang Ye, Jia Li, Yifei Song, Siwen Hu

“…In particular, when dealing with complex pore structures, the accuracy and performance of the SNESIM algorithm need further improvement. Future research will focus on optimizing the algorithm to handle more diverse pore structures and exploring 3D reconstruction methods to more comprehensively describe and analyze the pore characteristics in actual porous media.…”
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Machine Learning-Driven Prediction of Vitamin D Deficiency Severity with Hybrid Optimization by Usharani Bhimavarapu, Gopi Battineni, Nalini Chintalapudi

“…To enhance the capacity of the classification system to predict multiple classes, preprocessing procedures such as data reduction, cleaning, and transformation were used on the raw vitamin D dataset. The improved whale optimization (IWOA) algorithm was used for feature selection, which optimized weight functions to improve prediction accuracy. …”
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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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Optimization strategies for public health education based on ISSA and information system technology by Zhanyu Ye, Yifei Li, Yan Zhang

“…IntroductionAgainst the backdrop of rapid development of information technology, public health education is facing challenges such as uneven resource allocation and lagging content.MethodsTo propose an optimization strategy that can effectively improve the level of public health education, this study improves the sparrow search algorithm by introducing the theory of best point sets to optimize the allocation of public health education resources. …”
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An Improved Galerkin Framework for Solving Unsteady High-Reynolds Navier–Stokes Equations by Jinlin Tang, Qiang Ma

“…This error indicator guides an AMR algorithm that combines longest-edge bisection with local Delaunay re-triangulation, ensuring optimal mesh adaptation to complex flow features such as boundary layers and vortices. …”
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Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…The proposed WCAPSO-XGB model tunes the hyperparameters of XGBoost and classifies the credit scoring, and the experimental results are compared with various classifier such as Random Forest (RF), K-neighbors (KNN), Gaussian Naive Bayes (NB), AdaBoost, Gradient Boosting, Logistic Regression (LR), Neural Network (NN), Decision Tree (DT) and Linear Discriminant Analysis (LDA), and hyperparameter optimization methods, such as Grid Search (GS), Random Search (RS), Bays Optimization, Optuna Optimization, Hybrid Snake Optimizer Algorithm (HSOA), Exploratory Cuckoo Search, island Cuckoo Search (iCSPM and iCSPM2), and Improved SSA (ISSA) with HDPM, on four different datasets with a varying number of instances from small to large. …”
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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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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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