Forecast of water inrush quantity from coal floor based on genetic algorithm-support vector regression
Abstract：The problem of water inrush from coal floor was characterized by small samples,nonlinear,and using support vector regression algorithm avoided the limitations of qualitative analysis to predict the water inrush quantity.Support vector regression parameters optimization method was proposed based on genetic algorithm using the advantages of the global search capability of the genetic algorithm,and established genetic algorithm-support vector regression model of water inrush quantity prediction from coal floor.First,the model got the optimal support vector regression parameters by genetic algorithm to learn the training samples,and then used genetic algorithm-support vector regression model to predict the water inrush quantity of test samples.The test results show that,compared with the predictive values of neural network and the traditional support vector regression,the genetic algorithm-support vector regression model has higher prediction accuracy and good generalization ability.
Keywords：coal floorwater inrush quantity predictiongenetic algorithmsupport vector machinesupport vector regression
Publication Date：2011-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)