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Predictive Analysis of Temperature-Related Challenges in Bangladesh:

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dc.contributor.author Hasan, Md Akil
dc.contributor.author Rahman, Md. Mostafizur
dc.date.accessioned 2025-09-14T06:02:41Z
dc.date.available 2025-09-14T06:02:41Z
dc.date.issued 2024-07-24
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14453
dc.description Project report en_US
dc.description.abstract We are writing a paper based on the temperature in Bangladesh. Where we are working on a dataset from (2000-2022) that spans 23 years. We collected the data from NASA’s website(power data access viewer) [31] to help us build this project. We worked on this dataset from where we used some machine learning algorithms like ARIMA(Autoregressive Integrated Moving Average), ETS(Exponential Smoothing), Prophet, LSTM(Long short-term memory) where we tried to predict the surface temperature in future because of the temperature is increasing day by day and it is rising upwards and thus we tried to measure the temperature to predict how warmer the country of Bangladesh can get. This data collection is preprocessed and done by using machine learning algorithms to try and predict the best possible way of getting correct evaluation of data. Because of this rising temperature, we are trying to overcome the issues that we might encounter where people are facing many temperature related problems and vulnerabilities. And we will also provide some valuable insights from this project to deliver a better outcome to resolve these issues. And we are also hopeful to get a better value that can help us solve these problems by assessing the impact of rising temperatures. en_US
dc.description.sponsorship DIU en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Climate change en_US
dc.subject Machine learning en_US
dc.subject Rising temperatures en_US
dc.subject Climate modeling en_US
dc.title Predictive Analysis of Temperature-Related Challenges in Bangladesh: en_US
dc.title.alternative A Machine Learning Approach for Assessing the Impact of Rising Temperatures en_US
dc.type Other en_US


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