Rule-based expert system to assess caving output ratio in top coal caving

Abstract

Coal mining professionals in coal mining have recognized that the assessment of top coal release rate can not only improve the recovery rate of top coal, but also improve the quality of coal. But the process was often performed using a manual-based operation mode, which intensifies workload and difficulty, and is at risk of human errors. The study designs a assessment system to give the caving output ratio in top coal caving as accurately as possible based on the parameters adaptive Takagi-Sugeno (T-S) fuzzy system and the Levenberg-Marquardt (LM) algorithm. The main goal of the adaptive parameters based on LM algorithm is to construct its damping factor in the light of lowering of the objective function which is as taken as the index of termination iteration. The performance of the system is evaluated by Pearson correlation coefficient, Coefficient of Determination and relative error where the results of the Takagi-Sugeno method and the parameters adaptive Takagi-Sugeno method are compared to make the evaluation more robust and comprehensive.

Law of coal caving behind the flexible shield support in pseudo-inclined working face

“…The analysis process follows the principle that the loose range is the released range [ 30 , 31 ]. Suppose the loosening height of coal body at any time is h t , the vertical distance from coal discharge port to roof is h 0 , the part below h 0 is defined as lower coal body, and the part above h 0 is defined as upper coal body.…”

First Steps Towards Automatically Defining the Difficulty of Maze-Based Programming Challenges

“…To calculate the performance based on the data collected, we created a Fuzzy Rule-Based System (FRBS). The FRBS works by using rules to encode knowledge from a broad area into an automated system [40].…”

Optimization of the Process Parameters of Fully Mechanized Top-Coal Caving in Thick-Seam Coal Using BP Neural Networks

“…However, there are few quantitative studies on the process parameters of fully mechanized caving mining. In recent years, thanks to rapid developments in science and technology, advanced artificial intelligence and machine learning algorithms have been increasingly applied to coal production [20][21][22]. Fan YJ et al used a BP neural network to establish a safety evaluation model for coal mines and put forth an effective safety evaluation method for them [23].…”