Systematic Review of Deep Learning and Machine Learning Models in Biofuels Research

Sina Ardabili, Amir Mosavi, Annamária R. Várkonyi-Kóczy

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The importance of energy systems and their role in economics and politics is not hidden for anyone. This issue is not only important for the advanced industrialized countries, which are major energy consumers but is also essential for oil-rich countries. In addition to the nature of these fuels, which contains polluting substances, the issue of their ending up has aggravated the growing concern. Biofuels can be used in different fields for energy production like electricity production, power production, or for transportation. Various scenarios have been written about the estimated biofuels from different sources in the future energy system. The availability of biofuels for the electricity market, heating, and liquid fuels is critical. Accordingly, the need for handling, modeling, decision making, and forecasting for biofuels can be of utmost importance. Recently, machine learning (ML) and deep learning (DL) techniques have been accessible in modeling, optimizing, and handling biodiesel production, consumption, and environmental impacts. The main aim of this study is to review and evaluate ML and DL techniques and their applications in handling biofuels production, consumption, and environmental impacts, both for modeling and optimization purposes. Hybrid and ensemble ML methods, as well as DL methods, have found to provide higher performance and accuracy.

Original languageEnglish
Title of host publicationLecture Notes in Networks and Systems
PublisherSpringer
Pages19-32
Number of pages14
DOIs
Publication statusPublished - Jan 1 2020

Publication series

NameLecture Notes in Networks and Systems
Volume101
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

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Keywords

  • Big data
  • Biofuels
  • Deep learning
  • Machine learning models

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications

Cite this

Ardabili, S., Mosavi, A., & Várkonyi-Kóczy, A. R. (2020). Systematic Review of Deep Learning and Machine Learning Models in Biofuels Research. In Lecture Notes in Networks and Systems (pp. 19-32). (Lecture Notes in Networks and Systems; Vol. 101). Springer. https://doi.org/10.1007/978-3-030-36841-8_2