Journal ArticleDOI
Novel approach for forecasting the blast-induced AOp using a hybrid fuzzy system and firefly algorithm
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TLDR
The obtained R 2 and RMSE values show that FS-FA model has high prediction level in the modeling of blast-induced AOp, which clearly demonstrate the merits of the proposed FS- FA model.Abstract:
Air overpressure (AOp) produced by blasting is one of the environmental hazards of mining operations. Accordingly, the accurate prediction of AOp is very important, and this issue requires the application of appropriate prediction models. With this in view, this paper aims to propose a new data-driven model in the prediction of AOp using a hybrid model of fuzzy system (FS) and firefly algorithm (FA). This combination is abbreviated as FS-FA model. The used data-sets in the proposed FS-FA model were arranged in a format of three input parameters. In total, 86 sets of the mentioned parameters were prepared. To avoid over-fitting, the data-sets were divided into two parts of training (80%) and test sets (20%). Three quantitative standard statistical performance evaluation measures, variance account for (VAF), coefficient correlation (R2) and root mean squared error (RMSE), were used to check the accuracy of the FS-FA model. According to the results, the R2 and RMSE values obtained from the proposed FS-FA model were equal to 0.977 and 1.241 (for testing phase), respectively, which clearly demonstrate the merits of the proposed FS-FA model. In other words, the obtained R2 and RMSE show that FS-FA model has high prediction level in the modeling of blast-induced AOp.read more
Citations
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Slope stability prediction for circular mode failure using gradient boosting machine approach based on an updated database of case histories
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Random Forests and Cubist Algorithms for Predicting Shear Strengths of Rockfill Materials
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Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models
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A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural Network
TL;DR: The results indicated that the proposed FFA-ANN model was the most dominant model in comparison with other models (i.e., CART, SVM, KNN), and demonstrated that the FFA has a vital role in optimizing the ANN model in predicting blast-induced ground vibration.
References
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Firefly algorithms for multimodal optimization
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