Environmental Issues of Blasting: Applications of Artificial Intelligence Techniques

In: SpringerBriefs in Applied Sciences and Technology Ser.

Abstract

Intro -- About This Book -- Contents -- About the Authors -- 1 An Overview of Blasting Operations and Possible Techniques to Solve Environmental Issues of Blasting -- 1.1 Introduction -- 1.2 Blast Design -- 1.3 Environmental Effect Due to the Blasting -- 1.3.1 AOp or Air Blast -- 1.3.2 Ground Vibration -- 1.3.3 Flyrock -- 1.4 Blasting Effect Prediction -- 1.4.1 Prediction of AOp -- 1.4.2 Prediction of Ground Vibration -- 1.4.3 Prediction of Flyrock Distance -- 1.5 Prediction Methods by Computational Techniques -- 1.6 Blasting Solutions Enabled by the Blastiq™ Platform -- 1.6.1 Blast Design -- 1.6.2 Blast Control -- 1.6.3 BlastIQ™ Advanced Technologies -- 1.7 Conclusion Remarks -- References -- 2 Review of Empirical and Intelligent Techniques for Evaluating Rock Fragmentation Induced by Blasting -- 2.1 Introduction -- 2.2 Rock Fragmentation -- 2.3 Blastability -- 2.4 Fragmentation Measurement -- 2.5 Background of ML Models -- 2.5.1 Artificial Neural Network -- 2.5.2 Adaptive Neuro-Fuzzy Inference System (ANFIS) -- 2.5.3 Support Vector Machine (SVM) -- 2.5.4 Genetic Algorithm (GA) -- 2.6 Review of ML Models for Prediction of Rock Fragmentation -- 2.7 Discussion -- 2.8 Conclusion and Future Perspective -- References -- 3 Applications of AI and ML Techniques to Predict Backbreak and Flyrock Distance Resulting from Blasting -- 3.1 Introduction -- 3.2 Measurement of Flyrock -- 3.2.1 Flyrock -- 3.2.2 Backbreak -- 3.3 Concepts of Some AI Models -- 3.3.1 Artificial Neural Network (ANN) -- 3.3.2 ANFIS -- 3.3.3 Support Vector Machine (SVM) -- 3.3.4 ELM -- 3.3.5 PSO-ELM -- 3.4 Backbreak Prediction Using AI Techniques -- 3.5 Flyrock Prediction Using AI Techniques -- 3.6 Discussion -- 3.7 Conclusion -- References -- 4 Blast-Induced Air and Ground Vibrations: A Review of Soft Computing Techniques -- 4.1 Introduction -- 4.2 Ground Vibration -- 4.3 AOp.