Free convection effect on oscillatory flow using artificial neural networks and statistical techniques

Abo‐Dahab, S. M.; Ragab, Mahmoud; Elhag, Azhari A.; Abdel‐Khalek, S.

doi:10.1016/j.aej.2020.06.005

Cited by 7 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To develop a model, researchers input training data corresponding to correct output labels. The model was learned from the patterns in the training data [31,32]. After this, data that the model had not encountered yet were input to determine how the model performed [33].…”

Section: Decision Treementioning

confidence: 99%

[Retracted] Machine Learning Model and Statistical Methods for COVID‐19 Evolution Prediction

Alsulami

Abu-Zinadah

Ibrahim

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In this paper, we discuss the statistical processing of COVID-19 data. COVID-19 was initially recognized in Wuhan, China, on December 31, 2019. It then spread to other parts of the world, so it became known as a pandemic. It has received interest due to its sudden emergence as a deadly human pathogen. The effect is not only confined to morbidity and mortality but also extends to social and economic consequences. Statistical analysis is required to measure the damage done to humans and take the necessary measures to limit this damage. The objective of the work was to examine the effects of various factors on the deaths due to COVID-19. To achieve this goal, we applied a logistic regression (LR) model, as a statistical method, and a decision tree model, as a machine learning method, to model the deaths due to COVID-19 in France, Germany, Italy, and Spain. The predictive abilities of these two models were compared. The overall accuracies of the decision tree and LR were 94.1% and 93.9%, respectively. It was also observed that countries with high population densities tended to have more cases than those with smaller population densities. There were more female deaths than male deaths in the United Kingdom, and more deaths occurred for those aged 65 years and older. The data were collected from the World Health Organization’s official website from January 11, 2020, to May 29, 2020. The results obtained were in agreement with the previous results obtained by others.

show abstract

Section: Decision Treementioning

confidence: 99%

[Retracted] Machine Learning Model and Statistical Methods for COVID‐19 Evolution Prediction

Alsulami

Abu-Zinadah

Ibrahim

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…The impacts of using RCCs on the performance of the PV system are estimated by using an ANN-based method. The basics and foundations of the method are very well-established, while many different applications of ANNs in predicting the thermal performance of energy systems have been performed [ 52 , 53 , 54 , 55 , 56 ]. In the preset work, a 4-input/2-output system is considered, where the inputs are the Rew

, Rew

, Rc and Sc, while the outputs are the average and maximum PST.…”

Section: Resultsmentioning

confidence: 99%

Conjugate Heat Transfer Analysis for Cooling of a Conductive Panel by Combined Utilization of Nanoimpinging Jets and Double Rotating Cylinders

et al. 2023

View full text Add to dashboard Cite

In this work, double rotating active cylinders and slot nanojet impingement are considered for the cooling system of a conductive panel. Colder surface temperatures of the cylinders are used, while different rotational speeds are assigned for each of the cylinders. The impacts of cylinder rotational speeds, size and distance between them on the cooling performance are evaluated. The rotational effects and size of the cylinders are found to be very effective on the overall thermal performance. At the highest rotational speeds of the cylinders, the average Nusselt number (Nu) rises by about 30.8%, while the panel temperature drops by about 5.84 ∘C. When increasing the cylinder sizes, temperature drops become 7 ∘C, while they are only 1.75 ∘C when varying the distance between the cylinders. Subcooling and nanofluid utilization contributes positively to the cooling performance, while 1.25 ∘C and 10 ∘C temperature drops are found by varying the subcooled temperature and solid volume fraction. An artificial neural network is used for the estimation of maximum and average panel temperatures when double cylinder parameters are used as the input.

show abstract

“…The use of decision trees in machine learning is frequent. A test on an attribute is represented by each internal node, and each branch shows the outcome of the test [13,14]. A class label sheet is represented by each node (the decision taken after calculating all attributes).…”

Section: Decision Treementioning

confidence: 99%

Machine learning models to prediction OPIC crude oil production

et al. 2022

View full text Add to dashboard Cite

This paper aimed to compare the multi-layer perceptron as an artificial neural network and the decision tree model for predicting OPIC crude oil production. Machine learning is about designing algorithms that automatically extract valuable information from data, and it has seen many success stories. The accuracy of these two models was assessed using symmetric mean absolute percentage errors, mean absolute scaled errors, and mean absolute percentage errors. Achieved were the OPIC crude oil production's maximum projected figures. The OPIC crude oil output was also represented by certain descriptive scales and graphs; A comparison was made between the results and the earlier results acquired by the others after the study of the association between the variables revealed statistical significance.

show abstract

Free convection effect on oscillatory flow using artificial neural networks and statistical techniques

Cited by 7 publications

References 25 publications

[Retracted] Machine Learning Model and Statistical Methods for COVID‐19 Evolution Prediction

[Retracted] Machine Learning Model and Statistical Methods for COVID‐19 Evolution Prediction

Conjugate Heat Transfer Analysis for Cooling of a Conductive Panel by Combined Utilization of Nanoimpinging Jets and Double Rotating Cylinders

Machine learning models to prediction OPIC crude oil production

Contact Info

Product

Resources

About