Flood prediction using machine learning models

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Détails bibliographiques
Auteurs principaux:	Syeed, Miah Mohammad Asif, Farzana, Maisha, Namir, Ishadie, Ishrar, Ipshita, Nushra, Meherin Hossain
Autres auteurs:	Rahman, Tanvir
Format:	Thèse
Langue:	English
Publié:	Brac University 2022
Sujets:	Binary logistic regression Support Vector Classifier(SVC) K-Nearest Neighbor(KNN) Decision Tree Classifier(DTC) Flood prediction Rainfall Machine learning Artificial intelligence
Accès en ligne:	http://hdl.handle.net/10361/16635

id	10361-16635
record_format	dspace
spelling	10361-166352022-05-18T21:01:35Z Flood prediction using machine learning models Syeed, Miah Mohammad Asif Farzana, Maisha Namir, Ishadie Ishrar, Ipshita Nushra, Meherin Hossain Rahman, Tanvir Department of Computer Science and Engineering, Brac University Binary logistic regression Support Vector Classifier(SVC) K-Nearest Neighbor(KNN) Decision Tree Classifier(DTC) Flood prediction Rainfall Machine learning Artificial intelligence This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 25-26). Floods are one of nature’s most catastrophic calamities which cause irreversible and immense damage to human life, agriculture, infrastructure and socio-economic system. Floods are one of Bangladesh’s most common natural catastrophes, causing modest to large-scale devastation every year. As a poor-economy developing country, taking structural steps to manage floods in the world’s great rivers is a major problem. Several studies on flood catastrophe management and flood forecasting systems have been conducted. The accurate prediction of the onset and progression of floods in real time is challenging. To estimate water levels and velocities across a large area, it is necessary to combine data with computationally demanding flood propagation models. This paper aims to reduce the extreme risks of this natural disaster and also contributes to policy suggestions by providing a prediction for floods using different machine learning models. This prediction will be done by analyzing different parameters like temperature, area, water level, soil moisture, rainfall, etc which are some of the hydrological and climatic factors that influence flooding. This research will use Binary Logistic Regression, K-Nearest Neighbour (KNN), Support Vector Classifier (SVC), Decision tree Classifier and Stacked Generalization (Stacking) to provide an accurate prediction. With the outcome, a comparative analysis will be conducted to understand which model delivers a better accuracy. Miah Mohammad Asif Syeed Maisha Farzana Ishadie Namir Ipshita Ishrar Meherin Hossain Nushra B. Computer Science 2022-05-18T04:54:03Z 2022-05-18T04:54:03Z 2022 2022-01 Thesis ID 18101393 ID 18101665 ID 18101043 ID 18101573 ID 18101493 http://hdl.handle.net/10361/16635 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 26 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Binary logistic regression Support Vector Classifier(SVC) K-Nearest Neighbor(KNN) Decision Tree Classifier(DTC) Flood prediction Rainfall Machine learning Artificial intelligence
spellingShingle	Binary logistic regression Support Vector Classifier(SVC) K-Nearest Neighbor(KNN) Decision Tree Classifier(DTC) Flood prediction Rainfall Machine learning Artificial intelligence Syeed, Miah Mohammad Asif Farzana, Maisha Namir, Ishadie Ishrar, Ipshita Nushra, Meherin Hossain Flood prediction using machine learning models
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
author2	Rahman, Tanvir
author_facet	Rahman, Tanvir Syeed, Miah Mohammad Asif Farzana, Maisha Namir, Ishadie Ishrar, Ipshita Nushra, Meherin Hossain
format	Thesis
author	Syeed, Miah Mohammad Asif Farzana, Maisha Namir, Ishadie Ishrar, Ipshita Nushra, Meherin Hossain
author_sort	Syeed, Miah Mohammad Asif
title	Flood prediction using machine learning models
title_short	Flood prediction using machine learning models
title_full	Flood prediction using machine learning models
title_fullStr	Flood prediction using machine learning models
title_full_unstemmed	Flood prediction using machine learning models
title_sort	flood prediction using machine learning models
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/16635
work_keys_str_mv	AT syeedmiahmohammadasif floodpredictionusingmachinelearningmodels AT farzanamaisha floodpredictionusingmachinelearningmodels AT namirishadie floodpredictionusingmachinelearningmodels AT ishraripshita floodpredictionusingmachinelearningmodels AT nushrameherinhossain floodpredictionusingmachinelearningmodels
_version_	1814308240558653440

Flood prediction using machine learning models

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