Predicting temperature of major cities using machine learning and deep learning

Predicting temperature of major cities using machine learning and deep learning

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

Xehetasun bibliografikoak
Egile Nagusiak:	Jaharabi, Wasiou, Hossain, MD Ibrahim Al, Tahmid, Rownak, Islam, Md. Zuhayer, Rayhan, T.M. Saad
Beste egile batzuk:	Shakil, Arif
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Predicting temperature Time series analysis Recurrent neural networks Long short term memory networks Machine learning Cognitive learning theory
Sarrera elektronikoa:	http://hdl.handle.net/10361/23616

Antzeko izenburuak

An android application to predict human activity using a deep learning LSTM model
nork: Sikder, Debabrata
Argitaratua: (2024)

The influence of neuromarketing: machine learning based empirical analysis
nork: Muktadir, MD. Abdullah Al, et al.
Argitaratua: (2024)

Deep learning based predictive analytics for decentralized content caching in hierarchical edge networks
nork: Chakraborty, Dhruba, et al.
Argitaratua: (2022)

Conversion of Bengali speech to text using long short-term memory(LSTM)
nork: Chowdhury, Mohammad Fahim, et al.
Argitaratua: (2021)

Time-Series Forecasting of Ethereum Price using Long Short-Term Memory (LSTM) Networks
nork: Al-Wasee, Mohammad Samin, et al.
Argitaratua: (2022)

Economic crisis prediction due to pandemic outbreak using machine learning
nork: Ahmed, Tanvir, et al.
Argitaratua: (2021)

Leveraging sequential deep learning models for detecting multitude of human action categories
nork: Pranta, Kazi Al Refat, et al.
Argitaratua: (2024)

Economic crisis prediction due to pandemic outbreak using machine learning
nork: Ahmed, Tanvir, et al.
Argitaratua: (2021)

Sentiment analysis to determine employee job satisfaction using machine learning techniques
nork: Mouli, Nazifa, et al.
Argitaratua: (2023)

LSTM based content prediction for edge caching using federated learning approach
nork: Mazumder, Shafkat Ahmed, et al.
Argitaratua: (2021)

Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
nork: Biswas, Sunanda, et al.
Argitaratua: (2022)

Environmental monitoring with the help of Internet of Things (loT) and machine learning
nork: Alam, Md. Sakirul, et al.
Argitaratua: (2021)

Share market forecasting with LSTM neural network and sentimental trend prediction
nork: Rony, Ismail Hossain, et al.
Argitaratua: (2020)

Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
nork: Zaman, Md. Sayeed Ibne, et al.
Argitaratua: (2022)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
nork: Hossain, Shoumik, et al.
Argitaratua: (2022)

Malware Detection Using Neural Network
nork: Kayum, Syed Irfan, et al.
Argitaratua: (2021)

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

Modelling and forecasting energy demand of Bangladesh using AI based algorithms
nork: Mahmud, Booshra Nazifa, et al.
Argitaratua: (2019)

Short term forecasting of photovoltaic module using machine learning
nork: Nipa, Kainat, et al.
Argitaratua: (2022)

Comparative study on different methods to determine series resistance of PV module
nork: Sadia, Syeda Amana, et al.
Argitaratua: (2021)

Micro-learning modules are linked to enhanced retention of the learners and can be geared toward subconscious knowledge acquisition in an organization
nork: Siddique, Noman
Argitaratua: (2024)

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

Bang-lish sentiment classification using deep learning
nork: Saleheen, Abrar, et al.
Argitaratua: (2023)

Implementation of efficient fast charger using pulse-charging method and optimized temperature
nork: Sadmani, Saffat Newaz, et al.
Argitaratua: (2021)

Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA
nork: Chakraborty, Pranjal
Argitaratua: (2019)

Outdoor performance analysis and prediction of photovoltaic modules using machine learning algorithm
nork: Islam, Md. Kamrul, et al.
Argitaratua: (2021)

Differentiation through learning styles and memory /
nork: Sprenger, Marilee, 1949-
Argitaratua: (2003)

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

Machine learning-based approach on predicting online shopping addiction using EEG signals
nork: Nawer, Nafisa, et al.
Argitaratua: (2023)

Damaged road detection using Image Processing and Deep Learning
nork: Swadesh, Shimran Mahbub, et al.
Argitaratua: (2022)

Predicting crime using deep learning
nork: Shihab, Muhammad Nafees, et al.
Argitaratua: (2024)

A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium
nork: Ahmed, Istiak, et al.
Argitaratua: (2023)

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

Stock market prediction using ensemble learning
nork: Rabbani, Rakin Bin, et al.
Argitaratua: (2021)

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

Silent voice: harnessing deep learning for lip-reading in Bangla
nork: Shaheen, Munia, et al.
Argitaratua: (2024)

Rating detection by reviews using ML and NLP towards mobile phone recommendation
nork: Sarker, Md Wafi, et al.
Argitaratua: (2023)

Cooperative game theory based load balancing in long term evolution network
nork: Intesar, Sadia, et al.
Argitaratua: (2016)

Predicting regional accents of Bengali language using deep learning
nork: Ibrahim, Md. Abu, et al.
Argitaratua: (2022)

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