NDLI: Prediction of air-overpressure caused by mine blasting using a new hybrid PSO

Content Provider	Springer Nature Link
Author	Hasanipanah, Mahdi Shahnazar, Azam Bakhshandeh Amnieh, Hassan Jahed Armaghani, Danial
Copyright Year	2016
Abstract	The aim of the present study is to predict air-overpressure (AOp) resulting from blasting operations in the Shur river dam, Iran. AOp is considered as one of the most detrimental side effects induced by blasting. Therefore, accurate prediction of AOp is essential in order to minimize/reduce the environmental effects of blasting. This paper proposes a new hybrid model of particle swarm optimization (PSO) and support vector regression (SVR) for AOp prediction. To construct the PSO–SVR model, the linear (L), quadratic (Q) and radial basis (RBF) kernel functions were applied. Here, these combinations are abbreviated using PSO–SVR-L, PSO–SVR-Q and PSO–SVR-RBF. In order to check the accuracy of the proposed PSO–SVR models, multiple linear regression (MLR) was also utilized and developed. A database consisting of 83 datasets was applied to develop the predictive models. The performance of the all predictive models were evaluated by comparing performance indices, i.e. coefficient correlation (CC) and root mean square error (RMSE). As a result, PSO can be used as a reliable algorithm to train the SVR model. Moreover, it was found that the PSO–SVR–RBF model receives better results in comparison with other developed hybrid models in the field of AOp prediction.
Starting Page	23
Ending Page	31
Page Count	9
File Format	PDF
ISSN	01770667
Journal	Engineering with Computers
Volume Number	33
Issue Number	1
e-ISSN	14355663
Language	English
Publisher	Springer London
Publisher Date	2016-04-28
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Blasting operation Air-overpressure SVR PSO Hybrid model Computer-Aided Engineering (CAD, CAE) and Design Math. Applications in Chemistry Systems Theory, Control Calculus of Variations and Optimal Control; Optimization Classical Mechanics ApplicationMathematics/Computational Methods of Engineering
Content Type	Text
Resource Type	Article
Subject	Engineering Computer Science Applications Modeling and Simulation Software

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