Review of Anaerobic Digestion Modeling and Optimization Using Nature-Inspired Techniques

Anjali Ramachandran, Rabee Rustum, Adebayo J. Adeloye

Research output: Contribution to journalArticle

3 Citations (Scopus)
2 Downloads (Pure)

Abstract

Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.
Original languageEnglish
Article number953
JournalProcesses
Volume7
Issue number12
DOIs
Publication statusPublished - 13 Dec 2019

Keywords

  • anaerobic digestion
  • ant colony optimization
  • firefly algorithm
  • particle swarm optimization
  • genetic algorithm
  • artificial neural network
  • nature-inspired techniques

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science(all)
  • Environmental Science(all)

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