تصفح Chemical Engineering حسب الموضوع "Machine learning"
السجلات المعروضة 1 -- 9 من 9
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An integrated framework of data-driven, metaheuristic, and mechanistic modeling approach for biomass pyrolysis
( Elsevier , 2022 , Article)This study presents an integrated hybrid framework of data-driven (cascade forward neural network (CFNN)), metaheuristic (artificial bee colony (ABC)), and a mechanistic modeling (Aspen simulation) approach for the biomass ... -
Assessing the relation between mud components and rheology for loss circulation prevention using polymeric gels: A machine learning approach
( MDPI AG , 2021 , Article)The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce ... -
Data-driven modeling to predict the load vs. displacement curves of targeted composite materials for industry 4.0 and smart manufacturing
( Elsevier Ltd , 2021 , Article)This work presents an approach for smart manufacturing focusing on Industry 4.0 to predict the load vs. displacement curve of targeted cotton fiber/Polypropylene (PP) composite materials while complying with the required ... -
Development of a deep learning-based group contribution framework for targeted design of ionic liquids
( Elsevier , 2024 , Article)In this article, we present a novel deep learning-based group contribution framework for the targeted design of ionic liquids (ILs). This computational framework can expedite and improve the process of finding desirable ... -
Development of oil formation volume factor model using adaptive neuro-fuzzy inference systems ANFIS
( Society of Petroleum Engineers , 2021 , Conference)The oil formation volume factor is one of the main reservoir fluid properties that plays a crucial role in designing successful field development planning and oil and gas production optimization. The oil formation volume ... -
Optimal filler content for cotton fiber/PP composite based on mechanical properties using artificial neural network
( Elsevier Ltd , 2020 , Article)In this paper, a machine learning-based approach has been proposed to integrate artificial intelligence during the designing of fiber-reinforced polymeric composites. With the help of the proposed approach, an artificial ... -
Predicting carbonate formation permeability using machine learning
( Elsevier B.V. , 2020 , Article)It is imperative to characterize the formation permeability to simulate the flow behavior at subsurface conditions. An accurate characterization at the core scale is possible when large samples are available, but often ... -
Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves
( Elsevier Ltd , 2020 , Article)In this paper, artificial neural network (ANN) models are developed to predict the load-displacement curves for better understanding the behavior of cotton fiber/polyvinyl chloride (PVC) composites. Series of experiments ... -
State of charge estimation for a group of lithium-ion batteries using long short-term memory neural network
( Elsevier , 2022 , Article)The present paper estimates for the first time the State of Charge (SoC) of a high capacity grid-scale lithium-ion battery storage system used to improve the power profile in a distribution network. The proposed long ...
