Development of a novel hybrid intelligent model for solving engineering problems using GS-GMDH algorithm

• Published in: Engineering with computers Vol. 36; no. 4; pp. 1379 - 1391
• Main Authors: Jahed Armaghani, Danial, Hasanipanah, Mahdi, Bakhshandeh Amnieh, Hassan, Tien Bui, Dieu, Mehrabi, Peyman, Khorami, Majid
• Format: Journal Article
• Language: English
• Published: London Springer London 01.10.2020; Springer Nature B.V
• Subjects: Algorithms; Blasting; CAE) and Design; Calculus of Variations and Optimal Control; Optimization; Classical Mechanics; Computer Science; Computer-Aided Engineering (CAD; Control; Ground motion; Group method of data handling; Hybrid systems; Math. Applications in Chemistry; Mathematical and Computational Engineering; Mathematical models; Mining industry; Model accuracy; Model testing; Original Article; Performance evaluation; Predictions; Systems Theory; GS-GMDH; GMDH; Blasting; Ground vibration
• ISSN: 0177-0667; 1435-5663
• DOI: 10.1007/s00366-019-00769-2

This paper is aimed to develop and verify a novel hybrid intelligent model, which is indeed a new version of GMDH algorithm and named generalized structure of GMDH (GS-GMDH) to solve engineering problems. The proposed GS-GMDH model was validated its capability of predicting blast-induced ground vibration, a very important safety issues in the mining industry. For this regard, a data set with a totally of 96 samples was gathered from a blasting site in Shur River Dam region, Iran. Among them, 67 and 29 samples were used for constructing and testing the model, respectively. To check the accuracy and robustness of the proposed algorithm, the values of the performance evaluation measures, i.e., R 2 , variance accounted for (VAF), mean absolute error, root mean square error, scatter index, and Nash–Sutcliffe model efficiency ( E N–S ), were used. The results showed the efficiency of the GS-GMDH algorithm in the prediction of the blast-induced ground vibration. It was also confirmed that the proposed algorithm can be applied effectively to solving/predicting the engineering problems and it has also the potential to be generalized to other fields.