A Selective Survey Review of Computational Intelligence Applications in the Primary Subdomains of Civil Engineering Specializations

Author:

Demertzis Konstantinos1ORCID,Demertzis Stavros2,Iliadis Lazaros3ORCID

Affiliation:

1. Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, 25520 Orestiada, Greece

2. School of Spatial Planning, Development Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

3. Department of Civil Engineering, School of Engineering, Democritus University of Thrace, 67100 Kimmeria, Greece

Abstract

Artificial intelligence is the branch of computer science that attempts to model cognitive processes such as learning, adaptability and perception to generate intelligent behavior capable of solving complex problems with environmental adaptation and deductive reasoning. Applied research of cutting-edge technologies, primarily computational intelligence, including machine/deep learning and fuzzy computing, can add value to modern science and, more generally, to entrepreneurship and the economy. Regarding the science of civil engineering and, more generally, the construction industry, which is one of the most important in economic entrepreneurship both in terms of the size of the workforce employed and the amount of capital invested, the use of artificial intelligence can change industry business models, eliminate costly mistakes, reduce jobsite injuries and make large engineering projects more efficient. The purpose of this paper is to discuss recent research on artificial intelligence methods (machine and deep learning, computer vision, natural language processing, fuzzy systems, etc.) and their related technologies (extensive data analysis, blockchain, cloud computing, internet of things and augmented reality) in the fields of application of civil engineering science, such as structural engineering, geotechnical engineering, hydraulics and water resources. This review examines the benefits and limitations of using computational intelligence in civil engineering and the challenges researchers and practitioners face in implementing these techniques. The manuscript is targeted at a technical audience, such as researchers or practitioners in civil engineering or computational intelligence, and also intended for a broader audience such as policymakers or the general public who are interested in the civil engineering domain.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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