Journal
JOURNAL OF SCIENTIFIC COMPUTING
Volume 80, Issue 1, Pages 110-140Publisher
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10915-019-00935-0
Keywords
Sensitive fractional orders; Model error; Logarithmic-power law kernel; Petrov-Galerkin spectral method; Iterative algorithm; Parameter estimation
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Funding
- AFOSR Young Investigator Program (YIP) Award [FA9550-17-1-0150]
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Fractional differential equations provide a tractable mathematical framework to describe anomalous behavior in complex physical systems, yet they introduce new sensitive model parameters, i.e. derivative orders, in addition to model coefficients. We formulate a sensitivity analysis of fractional models by developing a fractional sensitivity equation method. We obtain the adjoint fractional sensitivity equations, in which we present a fractional operator associated with logarithmic-power law kernel. We further construct a gradient-based optimization algorithm to compute an accurate parameter estimation in fractional model construction. We develop a fast, stable, and convergent Petrov-Galerkin spectral method to numerically solve the coupled system of original fractional model and its corresponding adjoint fractional sensitivity equations.
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