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Fuzzy Clustering for Back-Calculation of Pavement Parameters

摘要

Artificial Intelligence and Fuzzy Sets theories have found a wide range of applications in engineering. In this paper, a fuzzy linear clustering method was applied to estimate the pavement parameters (moduli) from FWD deflection measurements. Back-calculation of pavement moduli is widely used in pavement design and maintenance. In pavement structural condi tion evaluation, surface deflection measurements are taken by using the Falling Weight Deflectometer (FWD test) at a number of locations. From these measurements and the forward model which describes surface deflection as a function of pavement structural parameters (moduli, thickness, etc.), estimation of pavement structure parameter values were "back-calculated". The formulation of the fuzzy clustering method was presented to solve the pavement moduli back-calculation problem. The experimental studies indicate that the fuzzy linear clustering method can achieve reasonably good prediction accuracy for the back-calculation task.

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