Topical treatments for skin conditions offer significant benefits, yet understanding the rheological characteristics of semi-solid formulations is crucial, as they directly influence treatment ...

The TensorDL-MPC toolbox is a Python-based software developed using the TensorFlow framework. It leverages deep learning techniques to enhance the performance of traditional Model Predictive Control ...

The development of predictive quantitative structure-activity relationship (QSAR) models using machine learning (ML) algorithms has become increasingly feasible due to the growing availability of ...

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Predictive models turn historical data into reliable forecasts that support accurate planning across industries. Different modeling types solve different problems, from forecasting numbers to ...

do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control and ...

Building systems are dynamic and non-linear. In HVAC systems, independently controlled modules interact, creating complex interdependencies that challenge optimizing energy savings and thermal comfort ...

Abstract: This paper involves the adoption of a multipurpose and easy-to-use Model Predictive Controller (MPC) written in Python and its interface with an industrial Programmable Logic Controller (PLC ...

Post-stroke epilepsy (PSE) is a critical complication that worsens both prognosis and quality of life in patients with ischemic stroke. An interpretable machine learning model was developed to predict ...

Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China School of Chemical Engineering, University of Chinese Academy of ...

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and ...