Evaluation of Machine Learning Approach in Flood Prediction Scenarios and Its Input Parameters: A Systematic Review
Date
2020
Authors
Nur-Adib Maspo
Aizul Nahar bin Harun
Masafumi Goto
Faizah Cheros
Nuzul
Azam Haron
Mohd Nasrun Mohd Nawi
Journal Title
Journal ISSN
Volume Title
Publisher
IOP Publishing
Abstract
This study aims to evaluate the existing machine learning (ML) approaches for flood prediction as well as evaluate parameters used for predicting flood, the evaluation is based on the review of previous research articles. In order to achieve the aim, this study is in two-fold; the first part is to identify flood prediction approaches specifically using ML methods and the second part is to identify flood prediction parameters that have been used as input parameters for flood prediction model. The main contribution of this paper is to determine the most recent ML techniques in flood prediction and identify the notable parameters used as model input so that researchers and/or flood managers can refer to the prediction results as the guideline in considering ML method for early flood prediction.
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Citation
Maspo, N. A., Harun, A. N. B., Goto, M., Cheros, F., Haron, N. A., & Nawi, M. N. M. (2020). Evaluation of Machine Learning approach in flood prediction scenarios and its input parameters: A systematic review. In IOP Conference Series: Earth and Environmental Science (Vol. 479, No. 1, p. 012038). IOP Publishing.