JSTOR Daily

Interpolation of Missing Temperature Data at Meteorological Stations Using P-BSHADE

ABSTRACT Some climate datasets are incomplete at certain places and times. A novel technique called the point estimation model of Biased Sentinel Hospitals-based Area Disease Estimation (P-BSHADE) is ...
JSTOR Daily

Variogram investigation of covariance shape within longitudinal data with possible use of a krigeage technique as an interpolation tool: Sheep growth data as an example

Irish Journal of Agricultural and Food Research, Vol. 53, No. 1 (2014), pp. 51-64 (14 pages) Most quantitative traits considered in livestock evolve over time and several continuous functions have ...
EurekAlert!

Big data in geochemistry for international research

Geochemistry was established as one of the central pillars of the geosciences by Victor Moritz Goldschmidt in Göttingen. It describes the formation and evolution of our planet, as well as the mass ...
IEEE

A Deep-Learning-Based Targeted Interpolation Method for Seismic Data: A Consecutively Missing Trace VSP Case

Abstract: Seismic data interpolation is an important processing method for improving the quality of seismic data. Traditional interpolation methods often face limitations due to their dependence on ...
Semiconductor Engineering

Data-driven RRAM device models using Kriging interpolation

“A two-tier Kriging interpolation approach is proposed to model jump tables for resistive switches. Originally developed for mining and geostatistics, its locality of the calculation makes this ...
GitHub

Python scripts demonstrating curve fitting and interpolation techniques, including polynomial fitting, spline interpolation, and least squares methods, with visual examples and ...

This repository contains interactive Python scripts that demonstrate classic interpolation and curve fitting (regression) techniques with clear visualizations. Each script asks for data points via the ...