Scientific Data Visualization via Hybrid Model based on Fractal Spline Interpolation

This research paper is devoted towards the development of a novel hybrid model and its application in the visualization of scientific data. A hybrid model GPRC FIF, based on the spline and fractal interpolation, is established having four parameters and one scaling factor in its description. Data dependent constraints are achieved on two parameters and one scaling factor to envisage the inherit shape (positive) of the data. While two parameters are kept free to provide the shape flexibility to the user. The proposed scheme is also implemented on few numerical data sets to demonstrate the proposed mathematical results graphically. Moreover, the comparative analysis of proposed method with two existing methods is also deliberated.