Coastal erosion index using AHP and ANN for coastal manager.

Abstract

Coastal erosion can be found on almost all of Malaysia's beaches, but it is particularly prevalent on the country's east coast. The problem of coastal erosion has been resolved through the use of a variety of methods and treatments that are tailored to the severity of the erosion. It is critical for coastal managers and responsible agencies to have an index of erosion that can be used as a guide in determining the level of erosion in a given area in order to design the appropriate mitigation and treatment measures. It is necessary to identify and categorize the factors contributing to coastal erosion. This study employed a literature review and expert feedback questionnaires to identify the primary factors contributing to coastal erosion. This paper put forward the combining method of the AHP and neural network for evaluating the weights of each influential parameter to coastal erosion. As a result of the analysis, AHP discovered that coastal structure was the most influential factor influencing coastal erosion, followed by human activity, waves, and wind with weights of 0.5333, 0.2404, 0.1804, and 0.0459, respectively, whereas ANN analysis also discovered that coastal structure was the most influential factor influencing erosion, followed by human activity, wind, and waves with weights of 0.612, 0.232, 0.082, and 0.074, respectively. Despite the fact that the results of the two analyses were quite different in terms of weights values, the results of both analyses allowed us to determine which factors are the most important in terms of erosion. The weighted application of these factors will be an additional guide to existing guidelines such as NCES and ISMP in evaluating appropriate coastal mitigation and planning strategies. The outcome of this study also able to enhance the coastal management in terms of being the early reference of coastal manager and stakeholders in developing or managing coastal areas.