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AVERAGE MONTHLY RAINFALL FORECAST IN ROMANIA BY USING k-NEAREST NEIGHBORS REGRESSION
| Content Provider | Semantic Scholar |
|---|---|
| Author | Cristian, Marinoiu |
| Copyright Year | 2018 |
| Abstract | The discovery of the best strategies for achieving future values forecast of a time series represents a permanent concern in time series analysis, highly motivated from a theoretical point of view, but especially from a practical point of view. In the context of the explosive growth of machine learning techniques, their usein time series forecast is a natural step to find modern alternatives to overcome existing limitations of traditional techniques. Although it is a relatively a simple method of learning, knn (k-nearest neighbor) regression seems to be a good competitor to traditional methods. The purpose of this paper is to describe how to use this method for forecasting time series and for achieving Monthly Average Rainfall (AMR) forecast in Romania. |
| Starting Page | 5 |
| Ending Page | 12 |
| Page Count | 8 |
| File Format | PDF HTM / HTML |
| Volume Number | 4 |
| Alternate Webpage(s) | http://www.utgjiu.ro/revista/ec/pdf/2018-04/4.pdf |
| Alternate Webpage(s) | http://www.utgjiu.ro/revista/ec/pdf/2018-04/01_marinoiu.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
