Accessible Requires Authentication Published by De Gruyter August 2, 2013

Artificial neural networks: applications in chemical engineering

Mohsen Pirdashti, Silvia Curteanu, Mehrdad Hashemi Kamangar, Mimi H. Hassim and Mohammad Amin Khatami

Abstract

Artificial neural networks (ANN) provide a range of powerful new techniques for solving problems in sensor data analysis, fault detection, process identification, and control and have been used in a diverse range of chemical engineering applications. This paper aims to provide a comprehensive review of various ANN applications within the field of chemical engineering (CE). It deals with the significant aspects of ANN (architecture, methods of developing and training, and modeling strategies) in correlation with various types of applications. A systematic classification scheme is also presented, which uncovers, classifies, and interprets the existing works related to the ANN methodologies and applications within the CE domain. Based on this scheme, 717 scholarly papers from 169 journals are categorized into specific application areas and general (other) applications, including the following topics: petrochemicals, oil and gas industry, biotechnology, cellular industry, environment, health and safety, fuel and energy, mineral industry, nanotechnology, pharmaceutical industry, and polymer industry. It is hoped that this paper will serve as a comprehensive state-of-the-art reference for chemical engineers besides highlighting the potential applications of ANN in CE-related problems and consequently enhancing the future ANN research in CE field.


Corresponding author: Silvia Curteanu, Faculty of Chemical Engineering and Environmental Protection, Department of Chemical Engineering, “Gheorghe Asachi” Technical University of Iasi, Str. Prof. dr. Doc. Dimitrie Mangeron, nr. 73, 700050 Iaşi, Romania. Tel.: +40 232 278 683, Fax: +40 232 271 311

This work was supported by the “Partnership in Priority Areas-PN-II” program, financed by ANCS, CNDI-UEFISCDI, Project PN-II-PT-PCCA-2011-3.2-0732, No. 23/2012.

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Received: 2013-4-17
Accepted: 2013-6-4
Published Online: 2013-08-02
Published in Print: 2013-08-01

©2013 by Walter de Gruyter Berlin Boston