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METHOD FOR ACCURATE STATE-WIDE WEATHER FORECASTING
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Abstract
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Specification
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ORDINARY APPLICATION
Published
Filed on 4 November 2024
Abstract
ABSTRACT A method (100) for accurate state-wide weather forecasting. Further, the method comprising collecting historical meteorological data from a designated source, including parameters such as temperature, humidity, wind speed, and rainfall for a specified region. Further, the method (100) comprising the steps of pre-processing the collected data to eliminate noise and fill missing values. The method (100) comprising the steps of generating weather predictions by applying a Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a Long Short-Term Memory (LSTM) model to the pre-processed data. Further, the method (100) comprising the steps of evaluating the performance of both models using metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) to determine the more accurate model. Further, the method (100) comprising the steps of providing the selected model's weather forecasts to end-users through an accessible interface
Patent Information
Application ID | 202411084278 |
Invention Field | COMPUTER SCIENCE |
Date of Application | 04/11/2024 |
Publication Number | 46/2024 |
Inventors
Name | Address | Country | Nationality |
---|---|---|---|
SOURAV SUTRADHAR | LOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI, G.T. ROAD, PHAGWARA, PUNJAB (INDIA) -144411 | India | India |
PRANAV PRAKASH | LOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI, G.T. ROAD, PHAGWARA, PUNJAB (INDIA) -144411 | India | India |
ASHISH JAMUDA | LOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI, G.T. ROAD, PHAGWARA, PUNJAB (INDIA) -144411 | India | India |
SUMANTA SAHA | LOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI, G.T. ROAD, PHAGWARA, PUNJAB (INDIA) -144411 | India | India |
Ms. RANJIT KAUR | LOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI, G.T. ROAD, PHAGWARA, PUNJAB (INDIA) -144411 | India | India |
Applicants
Name | Address | Country | Nationality |
---|---|---|---|
LOVELY PROFESSIONAL UNIVERSITY | JALANDHAR-DELHI, G.T. ROAD, PHAGWARA, PUNJAB (INDIA) -144411 | India | India |
Specification
Description:FIELD OF THE DISCLOSURE
[0001] This invention relates to the field of meteorological forecasting and, in particular, pertains to the application of machine learning (ML) and deep learning (DL) techniques for the accurate prediction of weather patterns at the state level, specifically focusing on the Telangana region of India.
BACKGROUND
[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] Accurate weather forecasting is essential for various sectors, including agriculture, disaster management, and transportation. Traditional f , Claims:1. A method (100) for method for accurate state-wide weather forecasting, the method comprising the steps of:
collecting historical meteorological data from a designated source, including parameters such as temperature, humidity, wind speed, and rainfall for a specified region;
pre-processing the collected data to eliminate noise and fill missing values;
generating weather predictions by applying a Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a Long Short-Term Memory (LSTM) model to the pre-processed data;
evaluating the performance of both models using metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) to determine the more accurate model; and
providing the selected model's weather forecasts to end-users through an accessible interface for decision-making in sectors such as agriculture, disaster management, and public health.
2. The method (100) as claimed in claim 1, wherein the weather predictions generated by the SARIMA model and the LSTM model are combin
Documents
Name | Date |
---|---|
202411084278-COMPLETE SPECIFICATION [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-DECLARATION OF INVENTORSHIP (FORM 5) [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-DRAWINGS [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-FIGURE OF ABSTRACT [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-FORM 1 [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-FORM-9 [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-POWER OF AUTHORITY [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-PROOF OF RIGHT [04-11-2024(online)].pdf | 04/11/2024 |
202411084278-REQUEST FOR EARLY PUBLICATION(FORM-9) [04-11-2024(online)].pdf | 04/11/2024 |
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