IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model
- Title
- IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model
- Creator
- Nithyashri J.; Poluru R.K.; Balakrishnan S.; Ashok Kumar M.; Prabu P.; Nandhini S.
- Description
- This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting. 2023 The Authors
- Source
- Measurement: Sensors, Vol-29
- Date
- 2023-01-01
- Publisher
- Elsevier Ltd
- Subject
- Deep reinforcement model; IoT; Prediction; Rainfall forecast
- Coverage
- Nithyashri J., Department of Computing Technologies, School of Computing, SRM Institute of Science and Technology, Chengalpet District, Kattankulathur, 603203, India; Poluru R.K., Department of Information Technology, Institute of Aeronautical Engineering, Hyderabad, India; Balakrishnan S., Department of Computer Science and Business Systems, Sri Krishna College of Engineering and Technology, Coimbatore, India; Ashok Kumar M., Faculty of Computer Science, Department of Computer Science and Software Engineering, Skyline University Nigeria, Kano, Nigeria; Prabu P., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Nandhini S., Department of Computer Science and Engineering, Karpagam Academy of Higher Education, Tamilnadu, Coimbatore, India
- Rights
- All Open Access; Gold Open Access
- Relation
- ISSN: 26659174
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Nithyashri J.; Poluru R.K.; Balakrishnan S.; Ashok Kumar M.; Prabu P.; Nandhini S., “IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model,” CHRIST (Deemed To Be University) Institutional Repository, accessed March 1, 2025, https://archives.christuniversity.in/items/show/14075.