Feb 27, 2020 · In this paper, three prevailing machine learning methods, ie Deep Neural Network (DNN), Support Vector Machine (SVM) and Gradient Boosting Decision Tree (GBDT) ...
Nov 15, 2020 · We implement and compare the performance of three machine learning methods including Deep Neural Network (DNN), Support Vector Machine (SVM) and ...
Dec 1, 2019 · In this paper, three prevailing machine learning methods, i.e. Deep Neural Network (DNN), Support Vector Machine (SVM) and Gradient Boosting ...
We compared two methods: Gilbert and DL algorithms. ... One of the novel methods for forecasting multiphase flow rate using deep learning was proposed by Alakeely ...
We implement and compare the performance of three machine learning methods including Deep Neural Network (DNN), Support Vector Machine (SVM) and ...
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Machine learning algorithms perform more efficiently than deep learning methods in classifying gas-liquid flow regimes in pipelines. Extreme gradient boosting ...
The obtained results indicate that the machine learning algorithms estimate oil, gas and water rates with acceptable accuracy. The feasibility of the data- ...
Aug 20, 2024 · Machine learning is revolutionizing multiphase flow modeling, offering new ways to predict complex behaviors and improve accuracy
Nov 29, 2021 · Regarding the algorithms, the Extra Trees model classifies the flow patterns with the highest degree of fidelity, achieving an accuracy of 98.8% ...
Oct 27, 2014 · This paper compares a very simple regression method (MLR), a classification method (random forest) and a back-propagation neural network (ANN).