Predicting climate induced floods using machine learning

Predicting climate induced floods using machine learning

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

Bibliografske podrobnosti
Main Authors:	Saleh, Chowdhury Nafis, Alam, Farhan, Khan, Md. Jawad
Drugi avtorji:	Shakil, Arif
Format:	Thesis
Jezik:	English
Izdano:	Brac University 2022
Teme:	Flood prediction Climate change Machine learning Artificial intelligence
Online dostop:	http://hdl.handle.net/10361/17160

Podobne knjige/članki

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
od: Toufique, S.M, et al.
Izdano: (2024)

Flood prediction using machine learning models
od: Syeed, Miah Mohammad Asif, et al.
Izdano: (2022)

Alumni opportunities using machine learning
od: Siaum, Arshif Sharlimin, et al.
Izdano: (2019)

Flood prediction using ensemble machine learning models
od: Rahman, Tanvir
Izdano: (2024)

Estimating flood susceptibility of Bangladesh in the future year using machine learning
od: Alim, Sakib Bin, et al.
Izdano: (2021)

Bank loan prediction using machine learning
od: Mahottam, Parthosarothi, et al.
Izdano: (2023)

Machine learning as an indicator for breast cancer prediction
od: Shadman, Tahsin Mohammed, et al.
Izdano: (2019)

Crop prediction based on geographical and climatic data using machine learning and deep learning
od: Alif, Al Amin, et al.
Izdano: (2019)

Investigation assistant with suspect anticipating intelligence
od: Abdullah, Saqueeb, et al.
Izdano: (2019)

Machine learning approach for improving decision support in ICU
od: Siddiquee, Mohib Billah, et al.
Izdano: (2019)

Use of machine learning and weather predictions to bridge the gap between consumer demands and the market requirements of food crops
od: Hasan, Raad, et al.
Izdano: (2021)

An effective real-time flood disaster management with automated GSM warning system
od: Faruk, Omar, et al.
Izdano: (2024)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
od: Islam, Zahedul, et al.
Izdano: (2023)

Predicting peak performance of a cricket player using machine learning and data analytics
od: Azam, Akif, et al.
Izdano: (2023)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
od: Rafat, Md. Tasbi, et al.
Izdano: (2023)

Application of machine learning in credit risk assessment: a prelude to smart banking
od: Dhruba, Mir Ishrak Maheer, et al.
Izdano: (2019)

Machine learning approach for ECG analysis and predicting different heart diseases
od: Tithi, Sushmita Roy, et al.
Izdano: (2019)

Comparison of machine learning techniques to predict cardiovascular disease
od: Jaber, Mir Mohammad, et al.
Izdano: (2019)

Real time performance analysis on DDoS attack detection using machine learning
od: Suvra, Debashis Kar, et al.
Izdano: (2021)

Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
od: Tasnia, Rifah, et al.
Izdano: (2024)

A machine learning approach to credit default prediction and Individual credit scoring
od: Rahman, Md. Jaber, et al.
Izdano: (2018)

Start up business solution using machine learning
od: Sohan, Saad Ahmed, et al.
Izdano: (2018)

Heart disease prediction using machine learning algorithms
od: Ali, Musfiq, et al.
Izdano: (2019)

Comparative analysis of machine learning models for the prediction of asthma disease among the cardiovascular disease patients
od: Jahan, Asif
Izdano: (2024)

Predicting depression in Bangladeshi undergraduates using machine learning
od: Choudhury, Ahnaf Atef, et al.
Izdano: (2019)

Machine learning for stress prediction
od: Salehin, Sherajus, et al.
Izdano: (2023)

Flight fare prediction using machine learning
od: Noyon, Md. Shaim Hosan, et al.
Izdano: (2024)

Weather Pattern Extraction using Statistical Methods & Machine Learning Techniques
od: Habib, Adria Binte
Izdano: (2021)

Developing a machine learning based prognostic model and a supporting web-based application for predicting the possibility of early diabetes and diabetic kidney disease
od: Amin, M.M. Shahriar, et al.
Izdano: (2021)

RED-LSTM: Real time emotion detection using LSTM
od: Labiba, Mansura Rahman, et al.
Izdano: (2023)

Predictive maintenance of HVAC system using supervised machine learning algorithms
od: Fahim, Md. Zubayer Ahmed, et al.
Izdano: (2021)

Forecasting Dhaka stock exchange prices using machine learning models: a Performance analysis
od: Alam, Md. Iftekharul, et al.
Izdano: (2024)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
od: Islam, Roman, et al.
Izdano: (2024)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
od: Ahmed, Md. Sabbir, et al.
Izdano: (2021)

A deep learning approach for prediction of ADHD using brain structure
od: Siam, Shafin Ahad, et al.
Izdano: (2024)

Heart attack prediction using machine learning and XAI
od: Ahsan, Mumtahina
Izdano: (2023)

Interpretable MOOC dropout prediction using different Ensemble Methods and XAI
od: Khan, Labib Hasan, et al.
Izdano: (2023)

Emotion analysis using machine learning model and deep learning model on DEAP dataset
od: Hasan, Anita, et al.
Izdano: (2022)

Impact of machine learning and deep learning on biomedical applications and healthcare industry
od: Kabir, Md Saif, et al.
Izdano: (2024)

Breast cancer prediction using different machine learning models
od: Khandker Al- Muhaimin, et al.
Izdano: (2020)