Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data
This paper aims to explore the use of various DDM methods for soil moisture retrieval, identifying the advantages and disadvantages of each, compare and evaluate the results for further study. The study looks into the advantages and disadvantages of each DDM method, summarizing the Root- Mean-Square...
| Main Authors: | , |
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| Format: | Proceeding |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc
2015
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/15197/ http://ir.unimas.my/id/eprint/15197/2/Comparison.pdf |
| _version_ | 1848837802815389696 |
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| author | Hephi, Liauw Chai, Soo See |
| author_facet | Hephi, Liauw Chai, Soo See |
| author_sort | Hephi, Liauw |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | This paper aims to explore the use of various DDM methods for soil moisture retrieval, identifying the advantages and disadvantages of each, compare and evaluate the results for further study. The study looks into the advantages and disadvantages of each DDM method, summarizing the Root- Mean-Square-Error (RMSE) to identify soil moisture condition. In this study, Neural Network Model, Fuzzy-Rule Model, Bayesian Model, Multiple Regression Model and Support Vector Machines (SVM) were reviewed. The Neural Network model performed better compared with other models, proven with the lowest number of RMSE. The SVM model also showed high potential, whereas the Bayesian, Multiple Regression and Fuzzy-Rule Based models showed higher RMSE values, which indicate higher difference in accuracy |
| first_indexed | 2025-11-15T06:45:27Z |
| format | Proceeding |
| id | unimas-15197 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:45:27Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers Inc |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-151972024-01-12T01:24:49Z http://ir.unimas.my/id/eprint/15197/ Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data Hephi, Liauw Chai, Soo See QA75 Electronic computers. Computer science This paper aims to explore the use of various DDM methods for soil moisture retrieval, identifying the advantages and disadvantages of each, compare and evaluate the results for further study. The study looks into the advantages and disadvantages of each DDM method, summarizing the Root- Mean-Square-Error (RMSE) to identify soil moisture condition. In this study, Neural Network Model, Fuzzy-Rule Model, Bayesian Model, Multiple Regression Model and Support Vector Machines (SVM) were reviewed. The Neural Network model performed better compared with other models, proven with the lowest number of RMSE. The SVM model also showed high potential, whereas the Bayesian, Multiple Regression and Fuzzy-Rule Based models showed higher RMSE values, which indicate higher difference in accuracy Institute of Electrical and Electronics Engineers Inc 2015-12-08 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/15197/2/Comparison.pdf Hephi, Liauw and Chai, Soo See (2015) Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data. In: 9th International Conference on IT in Asia (CITA), 04-05 August 2015, Sarawak, Malaysia. https://ieeexplore.ieee.org/document/7349833 DOI: 10.1109/CITA.2015.7349833 |
| spellingShingle | QA75 Electronic computers. Computer science Hephi, Liauw Chai, Soo See Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data |
| title | Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data |
| title_full | Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data |
| title_fullStr | Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data |
| title_full_unstemmed | Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data |
| title_short | Comparison of data driven models (DDM) for soil moisture retrieval using microwave remote sensing data |
| title_sort | comparison of data driven models (ddm) for soil moisture retrieval using microwave remote sensing data |
| topic | QA75 Electronic computers. Computer science |
| url | http://ir.unimas.my/id/eprint/15197/ http://ir.unimas.my/id/eprint/15197/ http://ir.unimas.my/id/eprint/15197/ http://ir.unimas.my/id/eprint/15197/2/Comparison.pdf |