| Summary: | 博士 === 國立臺灣大學 === 地質科學研究所 === 96 === The most commonly observed phenomena in nature, especially for geosciences, always demonstrate as the temporal and spatial dependent cases. Naturally, profiling the stochastic issues will be the key for addressing the process in cases and be the necessary steps in analysis. In general, for time-dependent problems, spectral analysis can be stochastically utilized to investigate the periodic fluctuation in the most cases that interested period can be considered in time domain. On the other hand, it is apparently that sampling manner and ways frequently dominants the judgments for the major task of observation and analysis. The exploration in geosciences can not be averted from the sampling by mankind or automatic records; uncertainty will grow in abundance to the some degree of extent corresonding to the different cases. This research demonstrates stochastic analysis of time domain and observation in geosciences. Spectral analysis and representation are used to investigate periodical time series and inversely inspect dominant factors in the considered model, respectively; differential analysis is manipulated to demonstrate the uncertainty assessment for the system. Descriptive statistics is generally used to summarize a crowd data; non-linear regression also cohere the stochastic data to the predictable level. There are nine applications associated with the major work for groundwater and seismic Rayleigh wave (four cases), and the secondary researches about hydrodispersive in hydrogeology, GPS observation for displacement, seabed marine volume assessment for CO2 deep sequestration, wind characterization, and long-term assessment of one-degree-freedom vibration for building have been completed. It shows that the methods can be well applied to the research in geosciences; the fruitful and consolidated results inspire one who is interested and concerns.
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