Design and Experiment of Obstacle Avoidance Mower in Orchard by Yi Yang, Yichuan He, Zhihui Tang, Hong Zhang

“…On the premise of simplifying the inter-plant obstacle avoidance mechanism into a two-dimensional model for kinematics analysis, the motion parameters of the key components of the machine were determined. …”
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Development and Validation of a Computer Vision-Based Tool for Automated 3D Dental Model Arch Prediction by Juan David Tamayo Quintero, Juan Bernardo Gómez Mendoza, Sonia Victoria Guevara Pérez

“…Future research could further refine this methodology by exploring advanced mathematical models and incorporating machine learning techniques to optimize the selection process.…”
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Forecasting monthly residential natural gas demand in two cities of Turkey using just-in-time-learning modeling. by Burak Alakent, Erkan Isikli, Cigdem Kadaifci, Tonguc S Taspinar

“…The JITL-GPR method is easy to use and optimize, and offers a reduction in forecast errors compared to traditional time series methods and a state-of-the-art combination model; therefore, it is a promising tool for NGD forecasting in similar settings.…”
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Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions by Giuseppe Miceli, Maria Grazia Basso, Elena Cocciola, Antonino Tuttolomondo

“…Yet, their reliance on operator expertise and subjective interpretation limits their full potential. AI, particularly machine learning and deep learning algorithms, has emerged as a transformative tool to address these challenges by automating image acquisition, optimizing signal quality, and enhancing diagnostic accuracy. …”
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Key technical indicators for stock market prediction by Seyed Mostafa Mostafavi, Ali Reza Hooman

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Integrated Method of Future Capacity and RUL Prediction for Lithium‐Ion Batteries Based on CEEMD‐Transformer‐LSTM Model by Wangyang Hu, Chaolong Zhang, Laijin Luo, Shanhe Jiang

“…Simultaneously, the sparrow search algorithm (SSA) was used to obtain the optimal value of the hyperparameter learning rate for the RUL prediction model. …”
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Prediction of the likelihood of conception after the first or second insemination in Chinese Holstein cows using milk Fourier-transform infrared spectroscopy by Chu Chu, Peipei Wen, Weiqi Li, Yikai Fan, Zhuo Yang, Chao Du, Dongwei Wang, Liangkang Nan, Haitong Wang, Chunfang Li, Wenli Yu, Ahmed Sabek, Wan Wen, Guohua Hua, Junqing Ni, Yabin Ma, Shujun Zhang

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A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV by HUANG Lei, QI Yin, CHEN Weihua, DU Xianfei, MA Bing, TANG Jizhou

“…Subsequently, it integrates with a three-dimensional mesh Kriging interpolation model and optimize the Kriging interpolation parameters through GridSearchCV, which is a gridsearch and K-folder cross-validation method in the Scikit-learn machine learning. …”
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A fuzzy logic based energy management model for solar PV-wind standalone with battery storage system by Nayebare Alfred, Venkataramana Guntreddi, Aliyu Nuhu Shuaibu, Mutiu Shola Bakare

“…Future research will focus on real-world implementation and enhancing predictive control through machine learning.…”
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Predicting iron contents in the Tamra-Douahria mining site using a deep neural network approach by Zohra Kraiem, Fathi Maalaoui, Salah Bouhlel, Chaouki Sadik, Ali Sdiri

“…For this purpose, 357 iron-rich samples collected in the Tamra-Douahria mining sub-district were used to train, test and validate the obtained models. Out of 357, 285 data sets were selected for training the algorithm while 72 data points were used for model testing and validation. …”
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Fog Computing and Industry 4.0 for Newsvendor Inventory Model Using Attention Mechanism and Gated Recurrent Unit by Joaquin Gonzalez, Liliana Avelar Sosa, Gabriel Bravo, Oliverio Cruz-Mejia, Jose-Manuel Mejia-Muñoz

“…We combine it with the Newsvendor model to determine optimal inventory levels. The system is integrated with fog computing to facilitate the rapid dissemination of information throughout the company. …”
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Production forecasting for normal pressure shale gas wells based on coupling of production decline method and LSTM model by HAN Kening, WANG Wei, FAN Dongyan, YAO Jun, LUO Fei, YANG Can

“…This approach combines shale gas well production decline models with Long Short-Term Memory（LSTM） neural network models, leveraging machine learning techniques and different decline models for improved accuracy. …”
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A severity classification model of cervical spondylotic radiculopathy symptoms based on MRI radiomics: A retrospective study. by Xi Wang, Qiaoli Tao, Huanwen Liu, Huangbo Lin, Honglai Zhang

“…The least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify the optimal subsets of radiomics features, which were subsequently used to develop a support vector machine (SVM) classification model. …”
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Novel neuromuscular controllers with simplified muscle model and enhanced reflex modulation: A comparative study in hip exoskeletons by Ali Reza Manzoori, Sara Messara, Andrea Di Russo, Auke Ijspeert, Mohamed Bouri

“…The modifications consist firstly of simplifications to the Hill-type virtual muscle model, resulting in a more straightforward formulation and reduced number of parameters; and second, using a finer division of gait subphases in the reflex modulation state machine, allowing for a higher degree of control over the shape of the assistive profile. …”
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Automated detection of spreading depolarizations in electrocorticography by Sreekar Puchala, Ethan Muchnik, Anca Ralescu, Jed A. Hartings

“…As determined by leave-one-patient-out cross-validation, optimal performance was achieved with a gradient-boosting model using 30 features computed from 400-s electrocorticography segments sampled at 0.1 Hz. …”
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Forecast of Photovoltaic Power Based on IWPA-LSSVM Considering Weather Types and Similar Days by Yilun XU, Binqiao ZHANG, Jing HUANG, Xiao XIE, Ruoxin WANG, Danqing SHEN, Lina HE, Kaifan YANG

“…The least squares support vector machine (lSSVM) was optimized by IWPA, and an IWPA-LSSVM based photovoltaic power prediction model was established considering weather types and similar days. …”
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Bayesian Neural Networks With Robust Feature Interpretation for Enhanced Compressive Strength Prediction of Ultra‐High‐Performance Concrete by Tao Zhang, Ji Hao, Jie Zhang, Lina Du, Yunhao Zhang, Wenbin Jiao

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Susceptibility assessment of freeze-thaw erosion induced debris flow using random forest, Eastern Tibetan Plateau by Yongjie Yang, Yongjie Yang, Yongjie Yang, Yuqi Zhang, Yuqi Zhang, Yuqi Zhang, Hai Huang, Hai Huang, Jinsong Zhu, Jinsong Zhu, Jinsong Zhu, Qiwei Lv, Qiwei Lv, Qiwei Lv, Jiang Peng, Jiang Peng

“…Control factors with high frequency and performance were selected from the perspectives of material sources, dynamic conditions, and hydrological factors, leading to an optimized selection strategy, and the Random Forest Algorithm was employed for susceptibility assessment (No Freeze-thaw erosion model, NFEM). …”
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Prediction of Spectral Response for Explosion Separation Based on DeepONet by Xiaoqi Chen, Zhanlong Qu, Yuxi Wang, Zihao Chen, Ganchao Chen, Xiao Kang, Ying Li

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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

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