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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Yasmen Samhan Abd Elwahab
Beni-Suef University

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A survey on predicting oil spills by studying its causes using deep learning techniques Mona Mohamed Nasr; Fahd Kamal Al-Sheref; Yasmen Samhan Abd Elwahab
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp580-589

Abstract

It’s so easy to know the accidents as it’s already happened and solving these accidents is immediately handled, but searching for a solution for these accidents, don’t deny the existence of reasons that made accidents happen. Knowing the source of accidents will help in avoiding them to occur in the future. It’s an important field in searching as some human lives depend on the safety of such a field, so it’s so important to use a powerful technique to define these reasons as the research point in spill accidents and predicting accidents and to predict the occurrence of the accident before its happening depending on its reasons that lead to that accident in past times so with similar conditions it might happen an accident but it needs a sufficient data and a powerful technique such as deep learning techniques that give very precise results and by using this tool an Intelligent Model will build to predict oil spilling. In this survey paper, related work will be discussed to enhance that work.
An intelligent oil accident predicting and classifying system using deep learning techniques Yasmen Samhan Abd ElWahab; Mona Mohamed Nasr; Fahad Kamal Al Sheref
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp460-471

Abstract

This study discusses the problem of oil and gas faults that lead to spills or explosions that lead to a lot of losses in human life, oil field extraction, and costs. Petrol is an important field in our lives because it controls all aspects of human life and their way of life, so our research focused on petrol and its problems in order to introduce a better way of life. The data used in this research was taken from the 3w database that was prepared by Petrobras, the Brazilian oil holding. The 9 classes classified in that work include the normal state that indicates the factors that will not lead to a problem. Deep learning classification techniques were used in this study. 99% accuracy was obtained in that model, and it refers to a successful prediction and classification of each class. Different results were observed when different hidden layers, optimizers, neurons, epochs, and activation functions were used. 99% was achieved when using Adam's optimizer and Tanh's activation function.
Co-Authors Fahad Kamal Al Sheref Fahd Kamal Al-Sheref Mona Mohamed Nasr