Models for analysis of water suitability by L. Makarchuk, T. Likhouzova

“…Each of these methods provides an opportunity to improve the model by selecting parameters, which was done. Three models are implemented: the DTC model using entropy when splitting a node, the Naive Bayes model with the best value of var_smoothing, and the KNN model with the optimal number of "neighbors". …”
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Dynamic Modeling and Parameter Optimization of Potato Harvester Under Multi-Source Excitation by Jianguo Meng, Zhipeng Li, Zheng Li, Yanzhou Li, Wenxia Xie

“…Based on the physical parameters of the harvester’s internal structure and the connection parameters between components, a 12-degree-of-freedom (12-DOF) dynamic model of the entire machine was constructed. The corresponding simulation model was created in a MATLAB/Simulink environment to analyze the vibration characteristics of each component during harvesting operations. …”
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Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions by Khaled M. Salem, Javier M. Rey-Hernández, A. O. Elgharib, Francisco J. Rey-Martínez

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Artificial intelligence optimizes the standardized diagnosis and treatment of chronic sinusitis by Yang-Yang Liu, Shao-Peng Jiang, Ying-Bin Wang

“…With the development of artificial intelligence (AI), more “AI + medical” application models are emerging. Many AI-assisted systems have been applied to the diagnosis and treatment of CRS, providing valuable solutions for clinical practice.ObjectiveThis study summarises the research progress of various AI-assisted systems applied to the clinical diagnosis and treatment of CRS, focusing on their role in imaging and pathological diagnosis and prognostic prediction and treatment.MethodsWe used PubMed, Web of Science, and other Internet search engines with “artificial intelligence”、“machine learning” and “chronic sinusitis” as the keywords to conduct a literature search for studies from the last 7 years. …”
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Application and optimization of BP prediction model driven by internet of things in tourism education by Qi Lv

“…Compared to support vector machine (SVM) and random forest (RF) models, the optimized BP model exhibits marked improvements in accuracy, precision, mean squared error, and prediction time. …”
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An optimized LSTM-based deep learning model for anomaly network intrusion detection by Nitu Dash, Sujata Chakravarty, Amiya Kumar Rath, Nimay Chandra Giri, Kareem M. AboRas, N. Gowtham

“…The presented model uses three optimization methods, i.e., Particle Swarm Optimization (PSO), JAYA, and Salp Swarm Algorithm (SSA), to optimize the hyperparameters of LSTM. …”
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Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market by Bingzi Jin, Xiaojie Xu

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Evaluation of mesoporous silica synthesized for green adsorption by modeling via machine learning and mass transfer by Minge Yang, Qiqing Yue, Junyi He

“…Hyper-parameter optimization was achieved through particle swarm optimization, allowing us to fine-tune the models for optimal results. …”
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COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

“…In order to detect high error rate and poor convergence of the water ecological chemical oxygen demand (COD) prediction model, combining the limit learning machine (ELM) model and whale optimization algorithm, CAWOA is improved by the sin chaos search strategy, while the ELM optimizes the parameters of the algorithm to improve convergence speed, thus improving the generalization performance of the ELM. …”
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Implementation of Artificial Intelligence in Agriculture to Optimize Irrigation by A. Yu. Fedosov, A. M. Menshikh

“…It is shown how the integration of machine learning models can provide intelligent irrigation management. …”
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Retraction notice to “A prediction model for the performance of solar photovoltaic-thermoelectric systems utilizing various semiconductors via optimal surrogate machine learning methods” [Eng.... by Hisham Alghamdi, Chika Maduabuchi, Abdullah Albaker, Ibrahim Alatawi, Theyab R. Alsenani, Ahmed S. Alsafran, Abdulaziz Almalaq, Mohammed AlAqil, Mostafa A.H. Abdelmohimen, Mohammad Alkhedher

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Overview of equipment maintenance support mission planning model and solution by YANG Liangliang, ZHAO Deyong, LIU Xiaoyong, LIU Jie, SHEN Zixuan

“…The research status of the optimization model of maintenance demand estimation and force formation, maintenance mission assignment optimization model, maintenance job scheduling optimization model, and the solutions of the heuristic solution and mixed intelligent solution methods were summarized. …”
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Predictive models based on machine learning to analyze the adoption of digital payments in Latin America and the Caribbean by Jiang Wagner Mamani Lopez, Antonio Víctor Morales Gonzales, Pedro Pablo Chambi Condori

“…This study aims to develop machine learning models to predict the adoption of digital payments in Latin America and the Caribbean using statistical data from the World Bank's Global Findex Database for 2021. …”
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Advanced hybrid machine learning based modeling for prediction of properties of ionic liquids at different temperatures by Saud Bawazeer

“…The main aim of this work is to study three significant machine learning models to estimate the surface tension of ionic liquids via advanced hybrid computational techniques. …”
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Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models by Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous

“…These results underline the potential of machine learning models to foster intelligent energy management and promote sustainable energy practices in smart cities.…”
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Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Va... by Hongxin Gao, Stefan Schneider, Raymond Hernandez, Jenny Harris, Danny Maupin, Doerte U Junghaenel, Arie Kapteyn, Arthur Stone, Elizabeth Zelinski, Erik Meijer, Pey-Jiuan Lee, Bart Orriens, Haomiao Jin

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A Systematic Method for the Calibration of FEA Model of Synchronous Reluctance Machines Considering Manufacturing Effects by Andrea Credo, Paolo Pescetto

“…A synchronous reluctance motor prototype is designed, manufactured, and experimentally characterized, and the measured flux and torque characteristics are exploited for ex-post calibrating the FEA model of the machine. This approach led to a reduction in torque estimation error from 18% to 4%, and an improvement of the flux maps evaluation, thus enhancing and validating the design procedure and permitting further optimization steps of machines with similar geometry and dimensions. …”
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Personalized Course Recommendation System: A Multi-Model Machine Learning Framework for Academic Success by Md Sajid Islam, A. S. M. Sanwar Hosen

“…This study introduces a hierarchical multi-model machine learning framework for personalized course recommendations, integrating five predictive models: Success Probability Model (SPM), Course Fit Score Model (CFSM), Prerequisite Fulfillment Model (PFM), Graduation Priority Model (GPM), and Recommended Load Model (RLM). …”
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Development of a machine learning-based surrogate model for friction prediction in textured journal bearings by Yujun Wang, Georg Jacobs, Shuo Zhang, Benjamin Klinghart, Florian König

“…To address this issue, this study develops a machine learning (ML)-based surrogate model to predict friction in textured journal bearings. …”
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Development of machine learning models to predict clinical outcome and recovery time in dogs with parvovirus enteritis by Negin Sanaei, Mohamad Zamani-Ahmadmahmudi, Seyed Mahdi Nassiri

“…In this study, we sought to develop models to predict clinical outcome and recovery time in dogs with CPV infection using 10 and 4 machine learning algorithms, respectively. …”
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