Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines
Ayush Sahu1
Satish Sinha2
Haider Banka2
1.Department of CSE,IIT(ISM),Dhanbad,Jharkhand 826004,India2.Department of Sustainability,Adani University,Ahmedabad,Gujrat 382421,India
摘要：One of the most dangerous safety hazard in underground coal mines is roof falls during retreat mining.Roof falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation operations.As a result,a reliable roof fall prediction model is essential to tackle such challenges.Different parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research issue.The National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof falls.Data acquired for 37 mines is limited due to several restrictions,which increased the likelihood of incomplete-ness.Fuzzy logic is a technique for coping with ambiguity,incompleteness,and uncertainty.Therefore,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of parameters.The performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of deter-mination(R2).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.
机标关键词：algorithmgeneticsearchminessystemfuzzyrateroof
论文发表日期：2024-02-28
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：11( 31-41 )
英文信息