How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…Time series data from 10 subjects walking under 13 conditions, with and without hip exoskeletons, were analyzed. Six ANN models, each corresponding to a nonlinear metric, were trained using the Levenberg–Marquardt backpropagation algorithm and compared with MLR models. …”
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Research on axial compensation precision puncture control method of prostate puncture robot by Li Bing, Zhu Junwu, Yuan Lipeng

“…Then, an improved adaptive particle swarm optimization (PSO) algorithm based on Levy Flight is proposed to identify parameters of this control model for puncture prostate in this article. …”
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Adaptive SDN switch migration mechanism based on coalitional game by Lan YAO, Julong LAN

“…The problem of poor control plane performance causes in software-defined Networking due to the unreasonable mapping relationship between controllers and switches.To address this issue,an adaptive switch migration mechanism based on coalitional game was proposed.First,comprehensively considering the controller resource utilization,control overhead,and flow establishment time,the switch migration problem was modeled as a combination optimization problem.Then,a game theory was introduced to design a distributed algorithm,where each controller ran control logic independently and implemented coalitional game between controllers to achieve an adaptive switch migration mechanism that adapted to traffic characteristics.The simulation results show that the proposed mechanism can better adapt to the flow characteristics,reduce the control traffic overhead by about 19% and the average flow settling time by 30%,and improve the controller resource utilization.…”
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Multi-core helper thread prefetching for irregular data intensive applications by Jian-xun ZHANG, Zhi-min GU, Xiao-han HU, Min CAI

“…Betweenness centrality algorithm was used as a case study, the multi-parameter prefetching model of helper thread and optimized instances were presented and evaluated on commercial CMP platforms Q6600 and I7, the average speedup of betweenness centrality algorithm at different input scale is 1.20 and 1.11 respectively. …”
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Integer linear programming for unsupervised training set selection in molecular machine learning by Matthieu Haeberle, Puck van Gerwen, Ruben Laplaza, Ksenia R Briling, Jan Weinreich, Friedrich Eisenbrand, Clémence Corminboeuf

“…Altogether, this work provides a practical algorithm to improve the performance of physics-inspired ML models and offers insights into the conceptual differences with existing training set selection approaches.…”
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Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion by Siming Deng, Jiale Zhu, Yang Hu, Mingfang He, Yonglin Xia

“…Furthermore, to enhance both training efficiency and parameter optimization capabilities of the model, we introduce a Multi-strategy Improved Coati Optimization Algorithm (MSCOA). …”
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Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China by Baoxin Zhao, Jingzhong Zhu, Youbiao Hu, Qimeng Liu, Yu Liu

“…The main purpose of this research is to apply the logistic regression (LR) model, the support vector machine (SVM) model based on radial basis function, the random forest (RF) model, and the coupled model of the whale optimization algorithm (WOA) and genetic algorithm (GA) with RF, to make landslide susceptibility mapping for the Ankang City of Shaanxi Province, China. …”
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Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control by Peng Ji, Fengrui Han, Yifan Zhao

“…The upper-level control module calculates the desired yaw rate and sideslip angle using the two-degree-of-freedom (2-DOF) vehicle model and estimates the road adhesion coefficient by using the singular-value optimized cubature Kalman filtering (CKF) algorithm; the middle-level utilizes the second-order sliding mode controller (SOSMC) as a direct yaw moment controller in order to track the desired yaw rate and sideslip angle while also employing a joint distribution algorithm to control the torque distribution based on vehicle stability parameters, thereby enhancing system robustness; and the lower-level controller performs optimal torque allocation based on the optimal tire loading rate as the objective. …”
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SGO enhanced random forest and extreme gradient boosting framework for heart disease prediction by Anima Naik, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Both models are further optimized through hyperparameter tuning using the Social Group Optimization (SGO) algorithm. …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…We carefully split the reference data into training and test sets, allowing for independent and robust model validation. Feature selection included an initial screening for multicollinearity using correlation-based feature pruning, followed by final selection using a genetic algorithm. …”
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Detection of Tomato Leaf Pesticide Residues Based on Fluorescence Spectrum and Hyper-Spectrum by Jiayu Gao, Xuhui Yang, Simo Liu, Yufeng Liu, Xiaofeng Ning

“…In order to improve the operating rate of discrimination, a continuous projection algorithm (SPA) was used to extract the characteristic wavelengths of the fluorescence spectra and hyperspectral data of pesticide residues, and algorithms such as the least-squares support vector machine (LSSVM) algorithm and least partial squares regression (PLSR) were used to build a quantitative model, while algorithms such as the convolutional neural network (BPNN) algorithm and decision tree algorithm (CART) were used to build a qualitative model. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…The method first adapts the parameters of the variational modal noise reduction algorithm using an improved sparrow optimization algorithm, and then reconstructs the original vibration signal with noise reduction. …”
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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

“…Hyperparameter tuning is achieved through the Bayesian optimization algorithm to identify the model parameter set that maximizes test set accuracy.ResultsAnalysis of the transformer fault case library reveals that the model proposed in this paper reduces diagnostic time by nearly half compared to traditional machine learning diagnosis models. …”
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Research review on intelligent object detection technology for coal mines based on deep learning by Fan ZHANG, Jiarong ZHANG, Haixing CHENG

“…How to improve the accuracy, model adaptability, and computational efficiency of mine object detection is an urgent research topic in the field of mining artificial intelligence. …”
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A New Hybrid MPPT Based on Incremental Conductance-Integral Backstepping Controller Applied to a PV System under Fast-Changing Operating Conditions by Ambe Harrison, Njimboh Henry Alombah, Jean de Dieu Nguimfack Ndongmo

“…Maximum power point tracking (MPPT) is becoming more and more important in the optimization of photovoltaic systems. Several MPPT algorithms and nonlinear controllers have been developed for improving the energy yield of PV systems. …”
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Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

“…It is believed that with the continuous optimization of algorithms and the improvement of computing power, DRL will play a more important role in the field of quantitative trading in financial market, providing more accurate and reliable support for investment decisions.…”
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A Multiobjective Incremental Control Allocation Strategy for Tailless Aircraft by Maoyu Su, Jianbo Hu, Yingyang Wang, Zihou He, Jiping Cong, Linxiao Han

“…In this way, the dependence on subjective experience is minimized based on the theory of Pareto optimal. Meanwhile, the huge computational burden that the intelligent optimization algorithm brings can also be avoided. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…The DSC index of the MTEF algorithm is 5.64% higher than that of the TransMorph algorithm. …”
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A Three-Dimensional Phenotype Extraction Method Based on Point Cloud Segmentation for All-Period Cotton Multiple Organs by Pengyu Chu, Bo Han, Qiang Guo, Yiping Wan, Jingjing Zhang

“…In addition, to address the challenge of accurately segmenting overlapping regions between different cotton organs, we introduced an optimization strategy that combines point distance mapping with curvature-based normal vectors and developed an improved region-growing algorithm to achieve fine segmentation of multiple cotton organs, including leaves, stems, and flower buds. …”
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Belief in building a full-fledged distance learning course in athletic training by Andrii Yefremenko, Illia Shutieiev

“…In particular, the experts mostly agreed with the logic and completeness of the course structure, the expediency of centralised content placement in the cloud environment, the optimality of the selected communication channels (email and cloud services), the clarity of the motor learning algorithm for remote performance by students, the adequacy of the proposed evaluation system and the presence of significant advantages in the use of tablets/smartphones in the educational process. …”
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