Weather Pattern Extraction using Statistical Methods & Machine Learning Techniques

Weather Pattern Extraction using Statistical Methods & Machine Learning Techniques

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

Bibliographische Detailangaben
1. Verfasser:	Habib, Adria Binte
Weitere Verfasser:	Ashraf, Faisal Bin
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2021
Schlagworte:	Statistical Methods Machine Learning Weather Prediction ARIMA Trend Analysis
Online Zugang:	http://hdl.handle.net/10361/15010

Ähnliche Einträge

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

Weather forecasting using Deep Learning
von: Fahad, Sheikh Abdul, et al.
Veröffentlicht: (2023)

Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models
von: Barua, Debalina
Veröffentlicht: (2023)

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

Machine learning based analysis and prediction of crop yield and prices of Aman, Aus and Boro rice
von: Bhattacharjee, Ruposri, et al.
Veröffentlicht: (2024)

Predicting climate induced floods using machine learning
von: Saleh, Chowdhury Nafis, et al.
Veröffentlicht: (2022)

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

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

Travel time prediction using machine learning and weather impact on traffic conditions
von: Deb, Bilash, et al.
Veröffentlicht: (2018)

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

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

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

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

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

Analyzing area-wise air pollution level using machine learning for a better future
von: Sihan, Sk. Atik Tajwar, et al.
Veröffentlicht: (2021)

Public vehicle ETA system using machine learning
von: Kabir, Md. Miraz, et al.
Veröffentlicht: (2018)

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

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

Real-time foul detection in football matches using machine learning techniques
von: Siddiqui, Bishal Sadi, et al.
Veröffentlicht: (2024)

Pattern recognition and machine learning /
von: Bishop, Christopher M.
Veröffentlicht: (2006)

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

Gene classification and pattern analysis using data mining and machine learning techniques
von: Ramisa, Aiman Jabeen, et al.
Veröffentlicht: (2021)

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

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

Observing mega cities to grow from space and predicting its growth using machine learning techniques
von: Chakma, Mitesh, et al.
Veröffentlicht: (2018)

Analysis of the impact of online education using EEG signals and machine learning algorithms
von: Hoque, Ehsanul, et al.
Veröffentlicht: (2021)

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

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
von: Tasnim, Anika, et al.
Veröffentlicht: (2022)

An implementation and analysis of deep learning models for the detection of wheat diseases
von: Zubair, Ahmad, et al.
Veröffentlicht: (2024)

Machine learning for stress prediction
von: Salehin, Sherajus, et al.
Veröffentlicht: (2023)

Statistical analysis of network data flows and predictions using statistical and machine learning regression models
von: Boateng, Albert, et al.
Veröffentlicht: (2024)

Water quality monitoring using machine learning and Internet Of Things (IoT)
von: Rahman, Naveed, et al.
Veröffentlicht: (2021)

Forecasting stock market prices using advanced tools of machine learning
von: Anwar, Md. Tawhid, et al.
Veröffentlicht: (2019)

Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
von: Ahmed, Sajjad
Veröffentlicht: (2019)

On weathering : the life of buildings in time /
von: Mostafavi, Mohsen
Veröffentlicht: (1993)

Application of CNN based architectures in detection of distracted drivers
von: Arafin, Irfana, et al.
Veröffentlicht: (2023)

A macroeconomic model for forecasting crude oil prices with Feedforward Neural Network Grid Search Experimentation
von: Aunjum, Md. Ragib, et al.
Veröffentlicht: (2021)

Fault detection in waste water treatment plant using statistical analysis & machine learning
von: Haque, Md. Ezazul, et al.
Veröffentlicht: (2019)

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

A machine learning approach to detect depression and anxiety using supervised learning
von: Ullas, Md Tahmidur Rahman, et al.
Veröffentlicht: (2019)