Principle of Maximum Entropy for back analysis in geotechnical engineering
Bin Chen
Abstract
Bin Chen
Abstract
Based on the modern information theory, two objective functions of the maximum likelihood method and Bayes' Method are deduced with random process and the Principle of Maximum Entropy. The theoretical significance of the deduction is that the maximum likelihood method and Bayes' Method are reconsidered according to the data information, and that one more reference is added to the back analysis which was performed only based on data and algorithms, thus, providing a new method for research of indeterminateness of back analysis.
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Based on the modern information theory, two objective functions of the maximum likelihood method and Bayes' Method are deduced with random process and the Principle of Maximum Entropy. The theoretical significance of the deduction is that the maximum likelihood method and Bayes' Method are reconsidered according to the data information, and that one more reference is added to the back analysis which was performed only based on data and algorithms, thus, providing a new method for research of indeterminateness of back analysis.
Key concepts: Principle of maximum entropy, Bayes' theorem, Maximum likelihood, Entropy (arrow of time), Mathematics, Maximum entropy spectral estimation, Maximum entropy thermodynamics, Statistics