Enhancing Agricultural Productivity through Machine Learning: A Model for Accurate Crop Yield Prediction by adlin jebaumari, jayanthila devi

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MODEL OF THE CONTROL SYSTEM ROCKING MACHINES OF OIL THE BASIC OF A SYNCHRONOUS ENGINES WITH THE SENSORLESS METHOD by T. I. Petrov, A. R. Safin, I. V. Ivshin, A. N. Tsvetkov, V. Yu. Kornilov

“…Mathematical models of all elements of the control station are presented: rocking machine, synchronous motor, vector control system.…”
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High-Frequency Cryptocurrency Price Forecasting Using Machine Learning Models: A Comparative Study by Fátima Rodrigues, Miguel Machado

“…This study addresses this challenge by developing a system for high-frequency forecasting of the closing prices of ten leading cryptocurrencies. We compare various machine learning models, including recurrent neural networks (RNNs), time series analysis (ARIMA), and conventional regression algorithms, using minute-step Bitcoin price data over a 30-day period to predict prices 60 min ahead. …”
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Shoreline dynamics prediction using machine learning models: from process learning to probabilistic forecasting by Afshar Adeli, Afshar Adeli, Ali Dastgheib, Ali Dastgheib, Dano Roelvink, Dano Roelvink, Dano Roelvink

“…Through comprehensive testing across one complex shoreline evolution scenario, this research identifies the ConvLSTM model—trained on 2D gridded data— as the optimal machine learning approach suited for addressing specific shoreline complexities and evolution patterns. …”
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Radiomics-based machine learning model for diagnosing internal abdominal hernias: a retrospective study by Zhong-Kai Ni, Tian-Han Zhou, Shu-Chao Kang, Ye-Hong Han, Hai-Min Jin, Shi-Fei Huang, Hai Huang

“…The performance of each model was assessed using the area under the curve (AUC), accuracy, and specificity to determine the optimal radiomics-based predictive algorithm. …”
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Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling by Kaida Cai, Xiaofang Yang, Zhengyan Wang, Wenzhi Fu, Hanwen Liu, Fatemeh Mahmoudi

“…The integration of feature selection further enhanced the machine learning models’ predictive capabilities. …”
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Solar energy prediction through machine learning models: A comparative analysis of regressor algorithms. by Huu Nam Nguyen, Quoc Thanh Tran, Canh Tung Ngo, Duc Dam Nguyen, Van Quan Tran

“…In this study, 5 machine learning models were used including: Gradient Boosting Regressor (GB), XGB Regressor (XGBoost), K-neighbors Regressor (KNN), LGBM Regressor (LightGBM), and CatBoost Regressor (CatBoost). …”
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Detecting Potential Investors in Crypto Assets: Insights from Machine Learning Models and Explainable AI by Timotej Jagrič, Davor Luetić, Damijan Mumel, Aljaž Herman

“…Data were collected through an online questionnaire distributed via social media and personal networks, yielding a limited but informative sample. Among the tested models, Efficient Linear SVM and Kernel Naïve Bayes emerged as the most optimal, balancing accuracy and interpretability. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…This study explores the application of advanced machine learning (ML) models to predict CO₂ solubility in NaCl brine, a critical parameter for effective carbon capture, utilization, and storage (CCUS). …”
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Development of a machine learning model for predicting renal damage in children with closed spinal dysraphism by Yu He, Wan-liang Guo, Ming-chang Zhang

“…This study aims to develop an effective machine learning model to predict renal damage in children with CSD. …”
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Technology for Improving the Accuracy of Predicting the Position and Speed of Human Movement Based on Machine Learning Models by Artem Obukhov, Denis Dedov, Andrey Volkov, Maksim Rybachok

“…Prediction of the person’s position (based on 10 previous frames) is performed using the DT model, which is optimal in terms of accuracy and computation time relative to other options. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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Domain shifts in industrial condition monitoring: a comparative analysis of automated machine learning models by P. Goodarzi, A. Schütze, T. Schneider

“…However, the overall performance significantly decreases when faced with domain shifts, such as transferring the trained model from one machine to another. In four out of seven datasets, FESC methods showed better results in the presence of domain shifts. …”
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Predicting postoperative nausea and vomiting using machine learning: a model development and validation study by Maxim Glebov, Teddy Lazebnik, Maksim Katsin, Boris Orkin, Haim Berkenstadt, Svetlana Bunimovich-Mendrazitsky

“…Feature importance analysis revealed that the performance of the proposed prediction tools aligned with previous clinical knowledge, indicating their utility. Conclusions The machine learning-based models developed in this study enabled improved PONV prediction, thereby facilitating personalized care and improved patient outcomes.…”
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EXAMINING THE IMPACT OF FEATURE SELECTION TECHNIQUES ON MACHINE AND DEEP LEARNING MODELS FOR THE PREDICTION OF COVID-19 by Hafiza Zoya Mojahid, Jasni Mohamad Zain, Marina Yusoff, Abdul Basit, Abdul Kadir Jumaat, Mushtaq Ali

“…This research aims to provide insights into the optimal integration of feature selection techniques with advanced machine learning models for accurate prediction of COVID-19 virus.…”

Knowledge Extraction via Machine Learning Guides a Topology‐Based Permeability Prediction Model by Jia Zhang, Gang Ma, Zhibing Yang, Jiangzhou Mei, Daren Zhang, Wei Zhou, Xiaolin Chang

“…Commonly used empirical formulas neglect its microscopic and topological characteristics, thus lacking accuracy and adaptability. While machine learning (ML) and deep learning (DL) models demonstrate promising performance, but encounter challenges of data availability, computational cost, and model interpretability. …”
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Study of model construction of fuel production from waste plastic pyrolysis based on machine learning by CHEN Sihan, YUAN Zhilong, WANG Ye, SUN Yifei*

“…A machine-learning approach was applied to utilize data from non-catalytic and molecular sieve catalytic processes and to build a model for analyzing raw material pyrolysis. …”
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Research on Prediction model of Carotid‐Femoral Pulse Wave Velocity: Based on Machine Learning Algorithm by Minghui Chen, Jing Xiong, Moran Li, Tao Hu, Yi Zhang

“…A Cox proportional hazards model revealed a significant association between machine learning‐predicted cf‐PWV and mortality risk, supporting the validity of prediction model. …”
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Prognostic machine learning models for thermophysical characteristics of nanodiamond-based nanolubricants for heat pump systems by Ammar M. Bahman, Emil Pradeep, Zafar Said, Prabhakar Sharma

“…This study compares prognostic machine learning (ML) models designed to predict the thermal conductivity and viscosity of nanolubricants used in HP compressors. …”
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Predicting the subclinical carotid atherosclerosis in overweight and obese patients using a machine learning model by D. V. Gavrilov, T. Yu. Kuznetsova, M. A. Druzhilov, I. N. Korsakov, A. V. Gusev

“…Aim. To develop a model for predicting the subclinical carotid atherosclerosis (SCA) in order to refine cardiovascular risk (CVR) using machine learning methods in overweight and obese patients without hypertension, diabetes and/or cardiovascular disease (CVD).Material and methods. …”
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