دورية أكاديمية
Intelligent decision support system based on rough set and fuzzy logic approach for efficacious precipitation forecast
| العنوان: | Intelligent decision support system based on rough set and fuzzy logic approach for efficacious precipitation forecast |
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| المؤلفون: | M. Sudha |
| المصدر: | Decision Science Letters, Vol 6, Iss 1, Pp 95-106 (2017) |
| بيانات النشر: | Growing Science, 2017. |
| سنة النشر: | 2017 |
| المجموعة: | LCC:Analysis |
| مصطلحات موضوعية: | Rough set, Fuzzy set, Parameter selection, Optimal reduct, Fuzzy rule learning, Analysis, QA299.6-433, Business mathematics. Commercial arithmetic. Including tables, etc., HF5691-5716 |
| الوصف: | Weather forecasting is essential and demanding scientific task of meteorological services across the world. It is a complex procedure that includes many specific technological field of study. The prediction is intricate process in meteorology because all decisions are made within a facet of uncertainty associated with weather systems. This research finding introduces a novel rough fuzzy computing approach for a short term rainfall forecasts. The model consists of rough set based optimal weather parameter selection module and fuzzy rule based classification module. The proposed fuzzy decision support model is compared with benchmarked classification approaches. The fuzzy classification model used in fuzzy decision support system is trained and tested using the reduct sets generated using proposed maximum frequency weighted feature reduction technique. The optimal reduct set constituting the weather parameters; minimum temperature, relative humidity and solar radiation achieved better prediction accuracy than complete feature set and the reducts. Most of the classification models have shown better accuracy when trained using the selected subsets of the target input. Thorough evaluation of the proposed model has revealed that coupling fuzzy decision support system and rough based pre-processing techniques was a better approach than traditional techniques. The experimental results revealed the proposed rough fuzzy model as a better rainfall prediction approach for modeling short range rainfall forecast. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1929-5804 1929-5812 |
| Relation: | http://www.growingscience.com/dsl/Vol6/dsl_2016_18.pdf; https://doaj.org/toc/1929-5804; https://doaj.org/toc/1929-5812 |
| DOI: | 10.5267/j.dsl.2016.6.002 |
| URL الوصول: | https://doaj.org/article/d2414a32721e48d69a9b4f2ed91e6cfc |
| رقم الأكسشن: | edsdoj.2414a32721e48d69a9b4f2ed91e6cfc |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19295804 19295812 |
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| DOI: | 10.5267/j.dsl.2016.6.002 |