RNN-GWR: A Geographically Weighted Regression Approach For Frequently Updated Data

In this study, to handle frequently updated data on given locations, a computationally efficient GWR approach, RNN-GWR, which utilizes reverse nearest neighbor (RNN) strategy, is proposed. The performance of the proposed RNN-GWR approach is compared with the performances of a Naïve-GWR and FastGWR approaches. Experimental evaluations show that the proposed approach is computationally efficient than the other approaches on handling frequently updated data.
Source: Neurocomputing - Category: Neuroscience Source Type: research