首页|Studies from Indian Institute for Technology in the Area of Machine Learning Reported (Efficient and Reliable Prediction of Dump Slope Stability In Mines Using Machine Learning: an In-depth Feature Importance Analysis)
Studies from Indian Institute for Technology in the Area of Machine Learning Reported (Efficient and Reliable Prediction of Dump Slope Stability In Mines Using Machine Learning: an In-depth Feature Importance Analysis)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Polska Akad Nauk
New research on Machine Learning is the subject of a report. According to news reporting originating from Kharagpur, India, by NewsRx correspondents, research stated, “This study rigorously examines the pressing issue of dump slope stability in Indian opencast coal mines, a problem that has led to significant safety incidents and operational hindrances. Employing machine to achieve a scientific goal of predictive accuracy for slope stability under various environmental and operational conditions.” Our news editors obtained a quote from the research from Indian Institute for Technology, “Promising accuracies were attained, notably with RF (0.98), SVM (0.98), and DT (0.97). To address the class imbalance issue, the Synthetic Minority Oversampling Technique (SMOTE) was implemented, resulting in improved model performance. Furthermore, this study introduced a novel feature importance technique to identify critical factors affecting dump slope stability, offering new insights into the mechanisms leading to slope failures.”
KharagpurIndiaAsiaCyborgsEmerging TechnologiesMachine LearningIndian Institute for Technology
NETL
NSTL
Polska Akad Nauk
