Article detail · 2019
MODELING OF GROUNDWATER LEVEL USING ARTIFICIAL INTELLIGENCE TECHNIQUES: A CASE STUDY OF REYHANLI REGION IN TURKEY
- Year
- 2019
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Applied Ecology and Environmental Research
- Catalog match (ISSN) Applied Ecology and Environmental Research
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
Determination of the change in groundwater level in terms of planning and managing resources is important. In this study, the groundwater level of Reyhanl region in Turkey was predicted using multi-linear regression (MLR), adaptive neural fuzzy inference system (ANFIS), Radial basis neural network (RBNN), support vector machines with radial basis functions (SVM-RBF) and support vector machines with poly kernels (SVM-PK) methods. Models were carried out using 192 data of monthly ground water level, monthly total precipitation and monthly average temperature values measured for 16 years between 2000 and 2015.
Topics
Citations
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39 citations
OpenAlex cited_by_count (cache / database)
8 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
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