Neural Networks in Civil Engineering: A Review

2009 ◽  
pp. 185-209 ◽  
Author(s):  
I. Flood
Keyword(s):  
Neural Networks ◽  
Civil Engineering

Artificial Neural Networks (ANNs) and Solution of Civil Engineering Problems

2020 ◽  
pp. 13-38
Author(s):  
Melda Yucel ◽  
Sinan Melih Nigdeli ◽  
Gebrail Bekdaş
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Structural Properties ◽  
Structural Design ◽  
Civil Engineering ◽  
Back Propagation ◽  
Training Algorithm ◽  
Design Problems ◽  
Engineering Problems ◽  
Artificial Neural

This chapter reveals the advantages of artificial neural networks (ANNs) by means of prediction success and effects on solutions for various problems. With this aim, initially, multilayer ANNs and their structural properties are explained. Then, feed-forward ANNs and a type of training algorithm called back-propagation, which was benefited for these type networks, are presented. Different structural design problems from civil engineering are optimized, and handled intended for obtaining prediction results thanks to usage of ANNs.

scholarly journals Importance of artificial neural networks in civil engineering: a systematic review of the literature

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Frank Jesús Valderrama Purizaca ◽  
Daniel Armando Chávez Barturen ◽  
Sócrates Pedro Muñoz Pérez ◽  
Victor A. Tuesta-Monteza ◽  
Heber Ivan Mejía-Cabrera
Keyword(s):  
Systematic Review ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Civil Engineering ◽  
Seismic Analysis ◽  
Ann Model ◽  
Review Of The Literature ◽  
Real Estate Valuation ◽  
Relevant Role ◽  
Artificial Neural

Artificial neural networks (ANN) have a relevant role nowadays; several areas apply this technique due to the advantages they have to solve complex problems with many constraints compared to traditional methods, which are becoming outdated. Very little is known about this technique and its application in different branches of Civil Engineering. For this reason, the present research aims to conduct a systematic review of the literature to identify the use of this technique and to determine the results of the application of ANN models in civil engineering. A total of 41 scientific articles were included, distributed as follows: 6 in Scopus, 1 in ScienceDirect, 23 in ProQuest, 7 in Google Scholar, 2 in DialNet, 2 in SciELO. It was found that ANNs are used to predict or forecast variables associated with the fields of study in civil engineering; 8 applications of ANN were found for concrete properties, 11 for soil properties, 5 for seismic analysis, 9 for hydraulics, 7 for real estate valuation and 1 for bridge design. Likewise, it was found that the multilayer Perceptron is the most used ANN model, achieving an average R2 of 0.99, which shows advantages to solve problems with precision, in shorter times, with missing data in the data sets, as well as the reduction of the error factor.

CONTRIBUTION OF AI TO THE CONSTRUCTION WORLD

2021 ◽  
Vol 12 (1) ◽  
pp. 58-70
Author(s):  
Kanhaiya Kumar ◽  
◽  
Muskan Kumari
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Simulated Annealing ◽  
Chaos Theory ◽  
Fuzzy Systems ◽  
Firefly Algorithm ◽  
Civil Engineering ◽  
Complicated Structure ◽  
Know How ◽  
Intelligent Computer

Artificial intelligence is a department of computer science and information technological know-how, involved in the research, layout, and application of intelligent computer. Conventional techniques for modeling and optimizing complicated structure systems require big amounts of computing assets, and artificial-intelligence-primarily based solutions can frequently provide treasured alternatives for successfully solving problems inside the civil engineering. This paper summarizes currently evolved methods and theories within the growing path for programs of synthetic intelligence in civil engineering, such as evolutionary computation, neural networks, fuzzy systems, professional machine, reasoning, type, and learning, in addition to others like chaos theory, cuckoo seek, firefly algorithm, know-how-based engineering, and simulated annealing. The primary studies tendencies are also talked about in the end. The paper presents an overview of the advances of synthetic intelligence carried out in civil engineering.

Artificial fuzzy neural networks in civil engineering

1996 ◽  
Vol 61 (2) ◽  
pp. 291-302 ◽  
Author(s):  
S. Rajasekaran ◽  
M.F. Febin ◽  
J.V. Ramasamy
Keyword(s):  
Neural Networks ◽  
Civil Engineering ◽  
Fuzzy Neural Networks ◽  
Fuzzy Neural

scholarly journals Artificial Neural Networks in Pavement Engineering: A Recent Review

2021 ◽  
Author(s):  
Abhishek Kurian ◽  
Elvin Sunildutt
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Deep Learning ◽  
Civil Engineering ◽  
Developed Countries ◽  
Pavement Management ◽  
Economic Management ◽  
Learning Techniques ◽  
Pavement Engineering ◽  
Artificial Neural

The application of Artificial Neural Networks (ANN) in civil engineering has increased drastically in the past few years. ANN tools are nowadays used commonly in developed countries over various fields of civil engineering like geotechnical, structural, traffic, pavement engineering etc. This paper deals with the review of recent advancements and utilization of ANNs in pavement engineering. The review will focus on pavement performance prediction, maintenance strategies, distress intensity detection through deep learning techniques, pavement condition index prediction etc. The use of ANNs in pavement management systems are expected to furnish a systematic schedule and economic management strategies in the field of pavement engineering. The use of ANNs combined with deep learning techniques help to address complex problems in pavement engineering and pave the way to a sustainable future.

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