Modelling and forecasting energy demand of Bangladesh using AI based algorithms

Modelling and forecasting energy demand of Bangladesh using AI based algorithms

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.

Opis bibliograficzny
Główni autorzy:	Mahmud, Booshra Nazifa, Ferdoush, Zannatul, Mim, Lamia Tasnim
Kolejni autorzy:	Chakrabarty, Amitabha
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2019
Hasła przedmiotowe:	Load forecast Prediction Decision tree Random forest K Nearest Long Short Term Memory Machine learning Decision trees
Dostęp online:	http://hdl.handle.net/10361/12353

Podobne zapisy

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
od: Rahee, Arnob, i wsp.
Wydane: (2021)

A feature selection approach to determine obesity using machine learning method
od: Antor, Shahidul Alam, i wsp.
Wydane: (2021)

Effectiveness of data mining in predicting heart diseases
od: Afrin, Shahria, i wsp.
Wydane: (2018)

A counseling system to predict the study path for freshmen
od: Usha, Rowshni Tasneem, i wsp.
Wydane: (2019)

Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
od: Zaman, Md. Sayeed Ibne, i wsp.
Wydane: (2022)

Detecting online recruitment fraud by using machine learning
od: Ghosh, Gitanjali, i wsp.
Wydane: (2021)

Predicting stock market movement using sentiment analysis of twitter feed
od: Chakraborty, Pranjal, i wsp.
Wydane: (2017)

Conversion of Bengali speech to text using long short-term memory(LSTM)
od: Chowdhury, Mohammad Fahim, i wsp.
Wydane: (2021)

Finding suitable locations for live campaigns using different machine learning techniques
od: Qudar, Mohiuddin Md. Abdul, i wsp.
Wydane: (2018)

Parking data analysis
od: Ahamed, Kasfi, i wsp.
Wydane: (2023)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
od: Tasnim, Anika, i wsp.
Wydane: (2022)

Flood prediction using machine learning models
od: Syeed, Miah Mohammad Asif, i wsp.
Wydane: (2022)

Share market forecasting with LSTM neural network and sentimental trend prediction
od: Rony, Ismail Hossain, i wsp.
Wydane: (2020)

Credit card fraud detection using machine learning techniques
od: Kabir, Tasmia, i wsp.
Wydane: (2021)

The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction
od: Mahmud, Mahmudul Hasan
Wydane: (2021)

A supervised learning approach by machine learning and deep learning algorithms to predict type II DM risk
od: Farabe, Abdullah Al, i wsp.
Wydane: (2021)

Cardiovascular disease prediction model using Machine Learning Algorithm
od: Arefin Mirdha, MD Shamsul
Wydane: (2023)

A voice signal based gender prediction model using random forest classifier
od: Ahmed, Saif, i wsp.
Wydane: (2018)

Economic crisis prediction due to pandemic outbreak using machine learning
od: Ahmed, Tanvir, i wsp.
Wydane: (2021)

Finding ideal geographical location for businesses using machine learning technique
od: Mahmud, Mir Ibtid, i wsp.
Wydane: (2022)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
od: Hossain, Shoumik, i wsp.
Wydane: (2022)

A machine learning approach on classifying orthopedic patients based on their biomechanical features
od: Hasan, Kamrul, i wsp.
Wydane: (2018)

Early grade prediction using profile data
od: Iqbal, Sumaiya, i wsp.
Wydane: (2021)

Performance analysis of machine learning algorithms for Malware classification
od: Bushra, Raisa Hasan, i wsp.
Wydane: (2023)

Machine learning-based approach on predicting online shopping addiction using EEG signals
od: Nawer, Nafisa, i wsp.
Wydane: (2023)

Amazon product reviews sentiment analysis using supervised learning algorithms
od: Hawladar, Mohibullah, i wsp.
Wydane: (2021)

Accuracy of data analysis on university student's major subject and job sector prediction using KNN and decision tree algorithm
od: Ahmed, Istear, i wsp.
Wydane: (2023)

Time-Series Forecasting of Ethereum Price using Long Short-Term Memory (LSTM) Networks
od: Al-Wasee, Mohammad Samin, i wsp.
Wydane: (2022)

Scrutiny of electricity data for consumption and load forecasting
od: Islam, Samiul
Wydane: (2018)

Machine learning for stress prediction
od: Salehin, Sherajus, i wsp.
Wydane: (2023)

Intelligent assisted living in pregnancy
od: Zaman, S. M. Tanveer, i wsp.
Wydane: (2022)

Automated fabric color prediction
od: Muhtashima, Fawzia, i wsp.
Wydane: (2024)

Application of CNN based architectures in detection of distracted drivers
od: Arafin, Irfana, i wsp.
Wydane: (2023)

Effects of warranty on purchase decision of electronic products: an empirical research from the perspective of Bangladesh
od: Ullah, G. M. Shafayet, i wsp.
Wydane: (2016)

Fighting depression: psychological approaches among Bangladeshi university students
od: Sen, Sanjib Kumar, i wsp.
Wydane: (2022)

Behavior trees in robotics and Al /
od: Collendanchise, Michele, i wsp.
Wydane: (2019)

Predicting brain age from EEG signals using machine learning and neural network
od: Pratanu, Abul Mushfique Muslah, i wsp.
Wydane: (2023)

An advanced hospital rating system using machine learning and natural language processing
od: Tamjid, Ali Asgar, i wsp.
Wydane: (2023)

Sentimental analysis of food review contents to improve food culture and the quality of virtual content using natural language processing and machine learning
od: Sarkar, Ripa, i wsp.
Wydane: (2024)

The influence of neuromarketing: machine learning based empirical analysis
od: Muktadir, MD. Abdullah Al, i wsp.
Wydane: (2024)