Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review
Flood disaster is a major disaster that frequently happens globally, it brings serious impacts to lives, property, infrastructure and environment. To stop flooding seems to be difficult but to prevent from serious damages that caused by flood is possible. Thus, implementing flood prediction could he...
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Online Access: | http://eprints.utm.my/id/eprint/89973/1/NurAdibMaspo2020_EvaluationofMachineLearningApproachinFlood.pdf http://eprints.utm.my/id/eprint/89973/ http://dx.doi.org/10.1088/1755-1315/479/1/012038 |
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my.utm.899732021-03-31T06:32:12Z http://eprints.utm.my/id/eprint/89973/ Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review Maspo, Nur Adib Harun, Aizul Nahar Goto, Masafumi Cheros, Faizah Haron, Nuzul Azam Mohd. Nawi, Mohd. Nasrun TA Engineering (General). Civil engineering (General) Flood disaster is a major disaster that frequently happens globally, it brings serious impacts to lives, property, infrastructure and environment. To stop flooding seems to be difficult but to prevent from serious damages that caused by flood is possible. Thus, implementing flood prediction could help in flood preparation and possibly to reduce the impact of flooding. 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. 2020-07-13 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/89973/1/NurAdibMaspo2020_EvaluationofMachineLearningApproachinFlood.pdf Maspo, Nur Adib and Harun, Aizul Nahar and Goto, Masafumi and Cheros, Faizah and Haron, Nuzul Azam and Mohd. Nawi, Mohd. Nasrun (2020) Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review. In: 7th AUN/SEED-Net Regional Conference On Natural Disaster 2019, RCND 2019, 25 November 2019 - 26 November 2019, Zenith Hotel Putrajaya, Malaysia. http://dx.doi.org/10.1088/1755-1315/479/1/012038 |
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TA Engineering (General). Civil engineering (General) Maspo, Nur Adib Harun, Aizul Nahar Goto, Masafumi Cheros, Faizah Haron, Nuzul Azam Mohd. Nawi, Mohd. Nasrun Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review |
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Flood disaster is a major disaster that frequently happens globally, it brings serious impacts to lives, property, infrastructure and environment. To stop flooding seems to be difficult but to prevent from serious damages that caused by flood is possible. Thus, implementing flood prediction could help in flood preparation and possibly to reduce the impact of flooding. 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. |
format |
Conference or Workshop Item |
author |
Maspo, Nur Adib Harun, Aizul Nahar Goto, Masafumi Cheros, Faizah Haron, Nuzul Azam Mohd. Nawi, Mohd. Nasrun |
author_facet |
Maspo, Nur Adib Harun, Aizul Nahar Goto, Masafumi Cheros, Faizah Haron, Nuzul Azam Mohd. Nawi, Mohd. Nasrun |
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Maspo, Nur Adib |
title |
Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review |
title_short |
Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review |
title_full |
Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review |
title_fullStr |
Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review |
title_full_unstemmed |
Evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review |
title_sort |
evaluation of machine learning approach in flood prediction scenarios and its input parameters: a systematic review |
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2020 |
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http://eprints.utm.my/id/eprint/89973/1/NurAdibMaspo2020_EvaluationofMachineLearningApproachinFlood.pdf http://eprints.utm.my/id/eprint/89973/ http://dx.doi.org/10.1088/1755-1315/479/1/012038 |
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13.188404 |