Reliability Prediction Based on Multi-State Dynamic Bayesian Network Structure Learning for Complex System With Time-Lagged Correlation by Kaixin Liu, Weilu Chen

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Multiscale Hjorth Descriptor on Epileptic EEG Classification by Achmad Rizal, Sugondo Hadiyoso, Suci Aulia, Inung Wijayanto, null Triwiyanto, Ziani Said

“…Simulation results showed that the Hjorth parameter on a scale of 1–15 yields 99.5% accuracy. …”
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Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics by Saima Rashid, Ayesha Siddiqa, Fekadu Tesgera Agama, Nazeran Idrees, Mohammed Shaaf Alharthi

“…Compartmental models have estimates of parameter complications, whereas machine learning algorithms struggle to understand MPV’s progression and lack elucidation. …”
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Analisis Perbandingan Algoritma SVM, KNN, dan CNN untuk Klasifikasi Citra Cuaca by Mohammad Farid Naufal

“…Hal ini dapat membantu pengembangan self autonomous machine agar tidak bergantung pada koneksi internet dan dapat melakukan kalkulasi sendiri secara real time. …”
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Software Design of Secondary Programmable and Debugging Development for Converter by 罗凌波, 戴计生, 尚敬

“…The detailed design process was described including parameter management, functional connectivity, online monitoring, main-circuit state machine, program updating and system security. …”
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袋式包装机横封切杆机构的设计与特性分析 by 郭志强, 朱茹敏, 李冬龙

“…The seals and crosscut mechanism is a basic and important actuating mechanism of bag packaging machine, usually its structure is designed to bar mechanism on experience and imitation. …”
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Hybridization of DEBOHID with ENN algorithm for highly imbalanced datasets by Sedat Korkmaz

“…Machine learning algorithms assume that datasets are balanced, but most of the datasets in the real world are imbalanced. …”
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"Numerical simulation and optimization of homogenization section screw based on response surface method " by WANG Yu-peng, XIN Jin-wei, MA Zi-chen, JIAN Ran-ran, MIAO Qing, ZENG Xian-kui

“…The regression equation obtained from the experiment was used to optimize the homogenization section structural parameters of the rubber injection machine rod. The results showed that the difference between the predicted values of each parameter obtained by simulation and the si-mulated values was within 2%. …”
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Prediction of permeability of amended soil using ensembled artificial intelligence models by Ankit Kumar, Rohit Ahuja

“…Sensitivity analysis reveals that Q is the most influential input parameter in predicting soil permeability.…”
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SIMULATION TEST FOR A PUSH-TYPE PRECISION METERING DEVICE BASED ON DISCRETE ELEMENT METHOD by Lingyu Liu, Xiangcai Zhang, Xiupei Cheng, Zhongcai Wei, Xianliang Wang

“…The discrete element method and a regression analysis were used to optimize the working parameters during the seed dropping stage. The optimal combination was found by the response surface optimization method, and both the seed dropping module and the whole machine were tested on a test bench with this parameter combination. …”
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Research on Remote Input/output Module Based on TCN by YANG Peng, WANG Li-de, YAN Xiang, SHEN Ping, WANG Kun

“…Besides, based on the presentation of overall structure and essential parameter, implementation mechanisms of VME slave finite state machine and structure of analog/digital signals communication in TCN was introduced in detail. …”
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RL–Fusion: The Large Language Model Fusion Method Based on Reinforcement Learning for Task Enhancing by Zijian Wang, Jiayong Li, Yu Liu, Xuhang Li, Cairong Yan, Yanting Zhang

“…Model fusion is a technique of growing interest in the field of machine learning, which constructs a generalized model by merging the parameters of multiple independent models with different capabilities without the need to access the original training data or perform costly computations. …”
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Aqua-MC as a simple open access code for uncountable runs of AquaCrop by Vahid Adabi, Hadi Ramezani Etedali, Asghar Azizian, Faraz Gorginpaveh, Ali Salem, Ahmed Elbeltagi

“…The study also highlighted that many parameters had low impact, suggesting that reducing the number of free parameters could enhance model efficiency. …”
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Biomechanical Analysis of <i>Camellia oleifera</i> Branches for Optimized Vibratory Harvesting by Rui Pan, Ziping Wan, Mingliang Wu, Shikui Lu, Lewei Tang

“…For the proposed empirical fitting equations, when the fitting parameter <i>k</i> is 168 ± 20 and the parameter <i>c</i> is 3.102 ± 0.421, the bending load–deflection relationship of the branches can be predicted more accurately. …”
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Differentiation of non-ST-segment elevation myocardial infarction from unstable angina using coronary computed tomography angiography: the role of imaging features and pericoronary... by Yang Lu, Qing Wang, Haifeng Liu, Qi Liu, Siqi Wang, Wei Xing

“…Four CCTA parameter models, encapsulating plaque parameters (model 1), plaque parameters + fatty attenuation index (FAI) (model 2), plaque parameters + CT fractional flow reserve (CT-FFR) (model 3), and plaque parameters + CT-FFR + FAI (model 4), were constructed. …”
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变杆长参数化四杆机构的运动学仿真 by 闫思江, 李凡国

“…Bsed on the commercial soft platform ADAMS,kinematics simulation model and the corresponding man-machine operation interface of hinge four bar linkage mechanism are established by the application of the parameter-driving technology.Through the modeling and motion simulation,the precisely and more efficiently mapping of four bar mechanism design are conveniently and quickly acquired,the function of drawing hinge four bar linkage mechanism curve map are achieved.So the accurate data of design is offered for four bar linkage mechanism design. …”
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Integral Sliding Mode Controller for PMSM Single Current Flux-Weakening Control by Cao Yu, Chi Song

“…An improved sliding mode speed controller was presented for flux-weakening control of permanent magnet synchronous machine (PMSM) based on single current regulation algorithm, to improve the controllability of the speed of the single current regulator. …”
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Predicting photodegradation rate constants of water pollutants on TiO2 using graph neural network and combined experimental-graph features by Mahia V. Solout, Jahan B. Ghasemi

“…The efficiency of photocatalytic reactions in degrading pollutants is influenced by several factors, making parameter optimization time-consuming. In this context, machine learning techniques provide an appropriate solution for designing optimal photocatalysts. …”
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Damage Simulation and Ultrasonic Detection of Asphalt Mixture under the Coupling Effects of Water-Temperature-Radiation by Yong-chun Cheng, Peng Zhang, Yu-bo Jiao, Ye-dan Wang, Jing-lin Tao

“…Splitting strength attenuation is defined as the damage parameter. In addition, the regression prediction models of the ultrasonic velocity and damage coefficient of asphalt mixture are constructed using the grey theory, neural network method, and support vector machine theory, respectively. …”
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A Review of Discrete Element Method Applications in Soil–Plant Interactions: Challenges and Opportunities by Yuyuan Tian, Zhiwei Zeng, Yuan Xing

“…Challenges such as long computation times and the complexity of determining accurate contact parameters are discussed, alongside emerging methods like machine learning that offer potential solutions. …”
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