Implementing machine learning techniques to forecast floods In Bangladesh based on historical data

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Détails bibliographiques
Auteurs principaux:	Toufique, S.M, Bhuiyan, Sadiq Uddin, Lateef, Ahmed, Zaman, Arman, Islam, Jubaer Bin
Autres auteurs:	Ziaul Karim, Dewan
Format:	Thèse
Langue:	English
Publié:	Brac University 2024
Sujets:	Machine learning Flood prediction Natural calamities Deep learning
Accès en ligne:	http://hdl.handle.net/10361/22779

Documents similaires

Predicting climate induced floods using machine learning
par: Saleh, Chowdhury Nafis, et autres
Publié: (2022)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
par: Rafat, Md. Tasbi, et autres
Publié: (2023)

An implementation and analysis of deep learning models for the detection of wheat diseases
par: Zubair, Ahmad, et autres
Publié: (2024)

An effective real-time flood disaster management with automated GSM warning system
par: Faruk, Omar, et autres
Publié: (2024)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
par: Islam, Roman, et autres
Publié: (2024)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
par: Islam, Zahedul, et autres
Publié: (2023)

Application of CNN based architectures in detection of distracted drivers
par: Arafin, Irfana, et autres
Publié: (2023)

Weather forecasting using Deep Learning
par: Fahad, Sheikh Abdul, et autres
Publié: (2023)

Machine learning as an indicator for breast cancer prediction
par: Shadman, Tahsin Mohammed, et autres
Publié: (2019)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
par: Alhossen, Md., et autres
Publié: (2021)

Flood prediction using ensemble machine learning models
par: Rahman, Tanvir
Publié: (2024)

Estimating flood susceptibility of Bangladesh in the future year using machine learning
par: Alim, Sakib Bin, et autres
Publié: (2021)

Use of machine learning and weather predictions to bridge the gap between consumer demands and the market requirements of food crops
par: Hasan, Raad, et autres
Publié: (2021)

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

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
par: Tasnim, Anika, et autres
Publié: (2022)

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
par: Turjo, Aquib Abtahi, et autres
Publié: (2021)

A modern technique to detect potholes by Computer Vision and Deep Learning
par: Saif, Muntasir Mahmud, et autres
Publié: (2023)

Real-time foul detection in football matches using machine learning techniques
par: Siddiqui, Bishal Sadi, et autres
Publié: (2024)

Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
par: Hasan, M. M. Kamrul, et autres
Publié: (2022)

Investigation assistant with suspect anticipating intelligence
par: Abdullah, Saqueeb, et autres
Publié: (2019)

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

Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
par: Fahim, Kaji Mehedi Hasan, et autres
Publié: (2024)

Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network
par: Rayhan, Mohammad, et autres
Publié: (2020)

Detecting self-esteem level and depressive indication due to different parenting style using supervised learning techniques
par: Al Taawab, Abdullah, et autres
Publié: (2022)

A deep learning approach towards soft biometrics attributes prediction using CNN
par: Kibria, Maharab, et autres
Publié: (2022)

Corn leaf disease detection using deep convolution neural network
par: Rabbi, Rawhatur, et autres
Publié: (2023)

Forecasting stock market prices using advanced tools of machine learning
par: Anwar, Md. Tawhid, et autres
Publié: (2019)

Real-time mastitis detection in livestock using deep learning and machine learning leveraging edge devices
par: Ghosh, Kawshik Kumar, et autres
Publié: (2023)

Empowering mobile network planning through deep learning: a path to democratization
par: Nabi, Syed Tauhidun
Publié: (2024)

Emotion analysis using machine learning model and deep learning model on DEAP dataset
par: Hasan, Anita, et autres
Publié: (2022)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
par: Ahmed, Md. Sabbir, et autres
Publié: (2021)

Heart disease prediction using machine learning algorithms
par: Ali, Musfiq, et autres
Publié: (2019)

An interpretable transformer based approach to classify Malaria from blood cell images
par: Islam, Mehafuza, et autres
Publié: (2023)

Fighting depression: psychological approaches among Bangladeshi university students
par: Sen, Sanjib Kumar, et autres
Publié: (2022)

A deep dive into node-level analysis with fusion RNN model for smart LTE network monitoring
par: Islam, Md Rashidul
Publié: (2024)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
par: Maliha, Miftahul Zannat, et autres
Publié: (2023)

A counseling system to predict the study path for freshmen
par: Usha, Rowshni Tasneem, et autres
Publié: (2019)

Predicting depression in Bangladeshi undergraduates using machine learning
par: Choudhury, Ahnaf Atef, et autres
Publié: (2019)

An efficient deep learning approach to detect skin Cancer
par: Islam, Ashfaqul, et autres
Publié: (2022)

Prostate cancer detection using deep learning neural network with transfer learning approach
par: Badhon, Ariful Islam Mahmud, et autres
Publié: (2022)