Summary of Building a Temperature Forecasting Model For the City with the Regression Neural Network (rnn), by Nguyen Phuc Tran et al.
Building a temperature forecasting model for the city with the regression neural network (RNN)
by Nguyen Phuc Tran, Duy Thanh Tran, Thi Thuy Nga Duong
First submitted to arxiv on: 27 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Systems and Control (eess.SY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a study on weather forecasting using recurrent neural networks (RNNs) in Vietnam, where environmental organizations have identified global warming as a pressing concern. Historically, limited weather monitoring stations and technological constraints hindered accurate predictions, making it challenging to develop reliable models. The research on predictive models in Vietnam has only gained momentum since 2000, leveraging advancements in computer science and mathematical modeling. This study applies machine learning techniques to RNNs, creating more accurate and reliable urban temperature forecasts. Key findings will be discussed, highlighting the importance of accurate weather predictions for informed decision-making. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about using special computers to predict the weather. The Earth is getting warmer, and scientists are trying to figure out what’s happening. A long time ago, it was hard to predict the weather because we didn’t have as many tools to collect data. Vietnam has been working on this problem more recently, starting around 2000. Now, they’re using special techniques called recurrent neural networks (RNNs) to make better predictions about urban temperatures. This study will show how RNNs can help us get better at predicting the weather and making important decisions. |
Keywords
» Artificial intelligence » Machine learning » Temperature
