A review of weather forecasting using LSTM model.
In: AIP Conference Proceedings, Jg. 2771 (2023-08-10), Heft 1, S. 1-7
Konferenz
Zugriff:
The aim of this paper is to present a review and an analytical study of Weather Forecasting of New Delhi using LSTM model. The requirement of correct and accurate predictions is very important especially considering the rate at which our modern day life goes. Different machine learning models can be used. Each model gives different results and the value of Root Mean Square Error (RMSE) actually determines as to how much accurate our own predictions are. The lesser the value of RMSE the more accurate the prediction values are and lesser is the error. Here LSTM model is used as we have to work on a large dataset which gives very accurate results over some different models like ARIMA model. LSTM is a basic non linear model of time series which learns nature of non-linearity from the data, which can makes the prediction more accurate as compared to ARIMA model which is a simple model and acts as a linear update model. [ABSTRACT FROM AUTHOR]
Titel: |
A review of weather forecasting using LSTM model.
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Autor/in / Beteiligte Person: | Sharma, Rishabh ; Gupta, Shashi Kant ; Mohialden, Yasmin Makki ; Jain, Priyanka Bhatewara ; Singh, Prabhishek ; Diwakar, Manoj ; Pandey, Shiv Dayal ; Kumar, Sarvesh |
Zeitschrift: | AIP Conference Proceedings, Jg. 2771 (2023-08-10), Heft 1, S. 1-7 |
Quelle: | 2023, Vol. 2771 Issue 1, p1-7. 7p.; Jg. 2771 (2023-08-10) 1, S. 1-7 |
Veröffentlichung: | 2023 |
Medientyp: | Konferenz |
ISSN: | 0094-243X (print) |
DOI: | 10.1063/5.0152493 |
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