Adaptive Neuro-Fuzzy Inference System for Predicting Shoreline Changes –A case study in Yilan of Taiwan
Date Issued
2014
Date
2014
Author(s)
Lai, Horng-Cherng
Abstract
Shoreline erosion is a worldwide problem that causes a major concern to the socio-economic developments in coastal cities for many countries. The increasingly intensive human activities along coasts enlarge coastal erosion areas and aggravate erosion processes, and thus cause land losses; moreover the global climate change in the past decades results in rising sea levels. Taiwan is frequently attacked by typhoons and shoreline erosion is a major concern to local residents. Shoreline change prediction has gained considerable attention; nevertheless, little consensus has been made on the best predictive methodology due to the complex heterogeneity of coastal geomorphology and sediment-transport processes. This study intends to model the shoreline change through investigating monthly shoreline position data collected from seven sandy beaches located at the Yilan County in Taiwan during 2004-2011. The harmonic analysis results indicate shorelines appear significantly periodic with great variation. The adaptive neuro-fuzzy inference system network (ANFIS) is configured with two scenarios, namely lumped and site specific, to extract significant features of shoreline changes for making shoreline position predictions in the next year. The lumped models for all stations are first investigated based on a number of possible input information, such as month, location, and the maximum and mean wave heights. The results, however, are not as favorable as expected, and wave heights do not contribute to modelling due to their high variability. Consequently, a site-specific model is constructed for each station, with its current position and nearby stations’ positions as model inputs, to predict its shoreline position in the next year. The results indicate that the constructed ANFIS models can accurately predict shoreline changes and can serve as a valuable tool for future coastline erosion warning and management.
Subjects
海岸變遷
海岸侵蝕
調適性網路模糊推論系統(ANFIS)
SDGs
Type
thesis
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