Title :
Analysis accuracy and robustness of parameters inversion in probability integral method by genetic algorithm
Author :
Zha Jian-feng ; Feng Wen-kai ; Zhu Xiao-jun ; Mi Li-qian
Author_Institution :
Sch. of Environ. Sci. & Spatial, China Univ. of Min. & Technol., Xuzhou, China
Abstract :
This paper focuses on accuracy and robustness of parameters inversion in probability integral method by genetic algorithm. For this, uniform design experimental method, subsidence prediction software and genetic algorithm program are used. Result shows that parameters in probability integral method can be retrieved precisely by genetic algorithm with relative errors of the retrieved parameters are less than 1.5%; retrieving parameters by genetic algorithm has a great applicability in different areas such as measuring errors, gross errors, loss of observation stations, etc.
Keywords :
genetic algorithms; mining; probability; genetic algorithm; parameters inversion; probability integral method; subsidence prediction software; uniform design experimental method; Accuracy; Algorithm design and analysis; Genetic algorithms; Monitoring; Prediction algorithms; Predictive models; Robustness; genetic algorithm; parameter inversion; probability integral method;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022281