Tạp chí
 
Năm 2017
 
Số 6 [12 - 2017], Năm thứ XXXI

Ứng dụng thuật toán rừng ngẫu nhiên để dự báo sóng va đập không khí sinh ra do nổ mìn trên mỏ than Đèo Nai

https://tapchi.hoimovietnam.vn/vi/archives?article=170612

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    Trường Đại học Mỏ - Địa chất

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  • Nhận bài: 25-07-2017
  • Sửa xong: 20-09-2017
  • Chấp nhận: 10-12-2017
  • Ngày đăng: 31-12-2017
Trang: 47 - 53
Lượt xem: 16
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Tóm tắt:

Mechanization Blasting method is one of the methods to break rock in open-pit mine and its effects is undeniable. Beside the advantages of the blasting method such as the large volume of rock is broken, can break any type of rock, not depending on the climate, etc then the disadvantages of this method include air-blast overpressure, ground vibration and fly rock. They can make vibration of works, broken the giass of the doors and affecting of residential and environmental damages. Most of open-pit mine have facing to these problems. The paper presents an approach using Random Forest machine learning algorithm to predict the air-blast overpressure caused by blasting operation at Đèo Nai coal mine, Quảng Ninh. The data used in this case study were collected from 146 explosions of the mine. The results showed that Random Forest is a suitable algorithm for predicting air-blast overpressure at Đèo Nai coal mine with RMSE=1.519147 và R2=0.941586. This study will help the blasters of Đèo Nai coal mine can adjust the parameters of blast fields and is the reference for the other open-pit mine, where the same condition with Đèo Nai coal mine.

Trích dẫn
Nguyễn Hoàng, Bùi Xuân Nam và Trần Quang Hiếu, 2017. Ứng dụng thuật toán rừng ngẫu nhiên để dự báo sóng va đập không khí sinh ra do nổ mìn trên mỏ than Đèo Nai, Tạp chí Công nghiệp Mỏ, số XXXI, kỳ 6, tr. 47-53.
Tài liệu tham khảo

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