Study on reciprocal relation of pore water pressure with genetic algorithm and neural network model(Contract research)

Seno, Shoji*; Kunimaru, Takanori; Nakajima, Makoto*; Toida, Masaru*; Watanabe, Kunio*; Sohail, A. R.*

At first, to exclude the influences of working of nature such as tide and atmospheric pressure from the source data, an analysis with Bayesian model was progressed. As the result of the estimation of these influences calculated by BAYTAP-G (Bayesian Tidal Analysis Program Grouping Model), it was found that the influence of the atmospheric pressure was comparatively large and that of tide was comparatively small.