2019
DOI: 10.1007/s42452-019-1749-9
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Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

Abstract: The soft computing techniques have been widely applied to model and analyze the complex and uncertain problems. This paper aims to develop a novel model for the risk assessment of tunneling projects using artificial bee colony algorithm. To this end, the risk of the second part of the Emamzade Hashem tunnel was assessed and analyzed in seven sections after testing geotechnical characteristics. Five geotechnical and hydrological properties of study zone are considered for the clustering of geological units in f… Show more

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Cited by 17 publications
(9 citation statements)
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“…There are no specific relations about most of these parameters, and they are determined based upon previous studies, experts, and trial and error. Hence, the selection pressure is dimensionless and has an impact on the sensitivity of the modeling error [75]. It is selected as 0.6 based upon the most recent studies.…”
Section: Binary Classification Modelling Using Gmdhmentioning
confidence: 99%
“…There are no specific relations about most of these parameters, and they are determined based upon previous studies, experts, and trial and error. Hence, the selection pressure is dimensionless and has an impact on the sensitivity of the modeling error [75]. It is selected as 0.6 based upon the most recent studies.…”
Section: Binary Classification Modelling Using Gmdhmentioning
confidence: 99%
“…The artificial intelligence is one of the most dynamic research areas for researchers. This method has many applications in different scientific and industrial fields, including pattern recognition, control systems, as well as signal and image processing (Dormishi, Ataei, Mikaeil, Khalokakaei, & Haghshenas, 2019; Haghshenas et al, 2019; Mikaeil, Bakhshinezhad, Haghshenas, & Ataei, 2019; Mikaeil, Beigmohammadi, Bakhtavar, & Haghshenas, 2019; Mikaeil, Haghshenas, Haghshenas, & Ataei, 2018; Mikaeil, Haghshenas, & Hoseinie, 2018; Mikaeil, Haghshenas, & Sedaghati, 2019; Noori, Mikaeil, Mokhtarian, Haghshenas, & Foroughi, 2020; Rad, Haghshenas, & Haghshenas, 2014; Rad, Haghshenas, Kanafi, & Haghshenas, 2012; Salemi, Mikaeil, & Haghshenas, 2018; Shirani Faradonbeh, Shaffiee Haghshenas, Taheri, & Mikaeil, 2019). Artificial neural network is one of the most commonly used components in the area of artificial intelligence which has experienced a significant growth in recent decades from both practical and theoretical aspects.…”
Section: Group Methods Of Data Handling‐type Neural Networkmentioning
confidence: 99%
“…Researchers were enabled to design advanced methods for solving various problems of real world inspired by the function of the human brain. Hence, artificial intelligence (AI) is considered one of the most successful achievements of computer science, simulating the behavior of the human brain in data analysis [45][46][47][48][49][50][51]. One of the AI branches is the artificial neural network (ANN).…”
Section: Artificial Neural Network (Ann)mentioning
confidence: 99%