Ye, Jinbi and Dalle, Juhriyansyah and Nezami, Ramin and Hasanipanah, Mahdi and Armaghani, Danial Jahed (2022) Stochastic fractal search-tuned ANFIS model to predict blast-induced air overpressure. Engineering with Computers, 38 (1). pp. 497-511. ISSN 0177-0667, DOI https://doi.org/10.1007/s00366-020-01085-w.
Full text not available from this repository.Abstract
Air overpressure (AOp) induced by rock blasting is an undesirable phenomenon in open-pit mines and civil construction works. The prediction of AOp has been always a complicated task since many parameters have potential to affect the propagation of air waves. This study aims to assess the capability of a new hybrid evolutionary model based on an integrated adaptive neuro-fuzzy inference system (ANFIS) with a stochastic fractal search (SFS) algorithm. To assess the reliability and acceptability of ANFIS-SFS model, the particle swarm optimization (PSO) and genetic algorithm (GA) were also combined with ANFIS. The proposed models were developed using a comprehensive database including 62 sets of data collected from four granite quarry sites in Malaysia. Performances of the ANFIS-SFS, ANFIS-GA, and ANFIS-PSO models were checked using statistical functions as the performance criteria. The obtained results showed that the proposed ANFIS-SFS model, with root mean square error of 1.223 dB, provided much higher generalization capacity than the ANFIS-PSO (RMSE of 1.939 dB), ANFIS-GA (RMSE of 2.418 dB), and ANFIS (RMSE of 3.403 dB) models in terms of predicting AOp. This clearly demonstrates the effectiveness of SFS to provide a more accurate model in the AOp prediction field.
| Item Type: | Article |
|---|---|
| Funders: | None |
| Uncontrolled Keywords: | Blasting; Air overpressure; ANFIS; Optimization algorithms |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering > Department of Civil Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 22 Apr 2022 08:29 |
| Last Modified: | 22 Apr 2022 08:29 |
| URI: | http://eprints.um.edu.my/id/eprint/33867 |
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