پیش بینی نرخ نفوذ برای مته ذره ای الماس توسط سیستم استنتاج فازی-عصبی تطبیقی و رگرسیون چندگانه

A database covering the rock properties and the machine operational parameters collected from seven different drilling sites in Turkey is constructed. Construction of an adaptive neuro-fuzzy inference system and the multiple regression models for predicting the penetration rate of diamond drilling is described. In the models, rock properties such as the uniaxial compressive strength, the rock quality designation, and the equipment operational parameters like bit load and bit rotation are considered. Although the prediction performance of multiple regression models is high, the adaptive neuro-fuzzy inference model exhibits better performance based on the comparison of performance indicators. By using the models, penetration rate of diamond bit drilling can be predicted effectively.