Estimating flood susceptibility of Bangladesh in the future year using machine learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

书目详细资料
Main Authors:	Alim, Sakib Bin, Lucky, Rakebun Islam, Ahmed, Aunindya Arif, Nahian, Prethu
其他作者:	Islam, MD Saiful
格式:	Thesis
语言:	English
出版:	Brac University 2021
主题:	Flood Susceptibility Machine Learning Flood in Bangladesh Linear Regression Model and Random forest Naive Bayes Theorem Artificial Neural Network
在线阅读:	http://hdl.handle.net/10361/15202

id	10361-15202
record_format	dspace
spelling	10361-152022022-01-26T10:18:16Z Estimating flood susceptibility of Bangladesh in the future year using machine learning Alim, Sakib Bin Lucky, Rakebun Islam Ahmed, Aunindya Arif Nahian, Prethu Islam, MD Saiful Syed, Shehran Anik, Marum Monem Department of Computer Science and Engineering, Brac University Flood Susceptibility Machine Learning Flood in Bangladesh Linear Regression Model and Random forest Naive Bayes Theorem Artificial Neural Network Machine Learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (page 29-30). Being a riverine country with more than 400 rivers, flood is a common phenomenon for Bangladesh. As, the land is less than five meters above sea level, and also due to heavy rainfall during monsoon season, it makes the country an easy target of flooding and about 30% of the total area is in danger level during this period. Additional to the yearly flooding, every 4 to 5 years there is a major flood occurs which covers more than 60% of the country. As of 22 July, 2020 alone, 102 upazila and 654 unions have been inundated in flood, affecting 3.3 million people, leaving 731,958 people water logged and a total of 93 deaths [2]. The aim of this research is to predict Bangladesh’s susceptibility to flooding so that the government as well as the people of this country can take necessary steps to lessen the effect. To predict the probability of flood we will be using some machine learning algorithm namely Linear Regression model, Random forest Regressor, Naive Bayes Theorem and Artificial Neural Network. This study is based on the data set from 1991-2013 water level and weather variables from Khulna districts Rupsa-Pasur station. Sakib Bin Alim Rakebun Islam Lucky Aunindya Arif Ahmed Prethu Nahian B. Computer Science 2021-10-11T04:36:17Z 2021-10-11T04:36:17Z 2021 2021-06 Thesis ID 21141068 ID 21141071 ID 17101225 ID 17301191 http://hdl.handle.net/10361/15202 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. 30 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Flood Susceptibility Machine Learning Flood in Bangladesh Linear Regression Model and Random forest Naive Bayes Theorem Artificial Neural Network Machine Learning
spellingShingle	Flood Susceptibility Machine Learning Flood in Bangladesh Linear Regression Model and Random forest Naive Bayes Theorem Artificial Neural Network Machine Learning Alim, Sakib Bin Lucky, Rakebun Islam Ahmed, Aunindya Arif Nahian, Prethu Estimating flood susceptibility of Bangladesh in the future year using machine learning
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Islam, MD Saiful
author_facet	Islam, MD Saiful Alim, Sakib Bin Lucky, Rakebun Islam Ahmed, Aunindya Arif Nahian, Prethu
format	Thesis
author	Alim, Sakib Bin Lucky, Rakebun Islam Ahmed, Aunindya Arif Nahian, Prethu
author_sort	Alim, Sakib Bin
title	Estimating flood susceptibility of Bangladesh in the future year using machine learning
title_short	Estimating flood susceptibility of Bangladesh in the future year using machine learning
title_full	Estimating flood susceptibility of Bangladesh in the future year using machine learning
title_fullStr	Estimating flood susceptibility of Bangladesh in the future year using machine learning
title_full_unstemmed	Estimating flood susceptibility of Bangladesh in the future year using machine learning
title_sort	estimating flood susceptibility of bangladesh in the future year using machine learning
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/15202
work_keys_str_mv	AT alimsakibbin estimatingfloodsusceptibilityofbangladeshinthefutureyearusingmachinelearning AT luckyrakebunislam estimatingfloodsusceptibilityofbangladeshinthefutureyearusingmachinelearning AT ahmedaunindyaarif estimatingfloodsusceptibilityofbangladeshinthefutureyearusingmachinelearning AT nahianprethu estimatingfloodsusceptibilityofbangladeshinthefutureyearusingmachinelearning
_version_	1814308754545442816

Estimating flood susceptibility of Bangladesh in the future year using machine learning

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