caa a22 4500 467931356 CHVBK 20180406152944.0 cr unu---uuuuu 170328e20060401xx s 000 0 eng 10.1007/s10706-004-7547-0 doi (NATIONALLICENCE)springer-10.1007/s10706-004-7547-0 A Comparative Analysis of Cognitive Systems for the Prediction of Drillability of Rocks and Wear Factor [Elektronische Daten] [T. Singh, A. Gupta, R. Sain] This paper demonstrates the applicability of cognitive systems or neural networks in predicting the drillibality of rocks and wear factor using engineering properties of rocks. Drillability of rocks is a useful guide for evaluating the suitability of drills for different ground operations. The wear factor of different materials subsequently helps in the selection of proper drills for different drilling operations. Different rocks were tested for Protodyakonov index, impact strength index, shore hardness number, Schmidt hammer number, drillability and micro bit chisels for wear factor. The data obtained from the tests were used to train and test the neural network. Results from the analysis demonstrate that cognitive systems are an effective tool in the prediction and suitability of drilling operations. Application of these predictive models can be a useful tool to obtain the value of these important parameters, they can save time and help to avoid the tedious process of instrumentation. Springer, 2006 cognitive systems nationallicence rock drillabilty nationallicence wear factor nationallicence resilient back propagation nationallicence Levenberg-Marquardt back propagation nationallicence one step secant back propagation nationallicence Singh T. Department of Earth Sciences, Institute for Technology, 400 056, Bombay, Mumbai - 76, Powai, India aut Gupta A. Institute of Technology, BHU, 05, Varanasi, India aut Sain R. Institute of Technology, BHU, 05, Varanasi, India aut Geotechnical & Geological Engineering Kluwer Academic Publishers 24/2(2006-04-01), 299-312 0960-3182 24:2<299 2006 24 10706 https://doi.org/10.1007/s10706-004-7547-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10706-004-7547-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Singh T. Department of Earth Sciences, Institute for Technology, 400 056, Bombay, Mumbai - 76, Powai, India aut NATIONALLICENCE 700 1- Gupta A. Institute of Technology, BHU, 05, Varanasi, India aut NATIONALLICENCE 700 1- Sain R. Institute of Technology, BHU, 05, Varanasi, India aut NATIONALLICENCE 773 0- Geotechnical & Geological Engineering Kluwer Academic Publishers 24/2(2006-04-01), 299-312 0960-3182 24:2<299 2006 24 10706 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer