In studies of irrigation and drainage projects for drainage, it is necessary to extend the data from the sampling point to the network. Therefore, based on available data from observational wells, estimating the state of hydraulic conductivity (K) in the surrounding area. The estimation process values for locations where there is no information for them based on viewing areas called wells spati...

The distributed measured data in large regions and remote locations, along with a need to estimate climatic for point sites where no have been recorded, has encouraged the implementation of spatial interpolation techniques. Recently, increasing use artificial intelligence become promising alternative conventional deterministic algorithms interpolation. present study aims evaluate some machine l...

Terrain is an ordered surface where locations relate to each other through their elevations. Preservation of this topographic orderliness by an interpolation method so that “if point A is higher than point B in the terrain, the interpolated elevation of A remains higher” is important to assure the practical value of the resultant DEM. Based on the concepts in group theory, this paper points out...

This paper connects two thoroughly investigated universal approximator techniques to each other. Recently, it has been shown that the input-output function of the general fuzzy KH interpolation method [1, 2] as well as its modification [3] are stable in the mathematical sense, or in other words, they can be considered as universal approximators with respect to the Lp (p ∈ [1,∞]) norm in the spa...

Aiming to reduce the drawbacks of traditional VIRE approach, such as inaccurate boundary positioning and poor results of virtual tags using linear interpolation, we propose a new algorithm based on Radial Basis Functions (RBF) interpolation method and Quantum-behaved Particle Swarm Optimization (QPSO) in this paper. In order to simulate the actual loss of RSSI better, the proposed approach uses...

For interpolation of scattered multivariate data by radial basis functions, an \uncertainty relation" between the attainable error and the condition of the interpolation matrices is proven. It states that the error and the condition number cannot both be kept small. Bounds on the Lebesgue constants are obtained as a byproduct. A variation of the Narcowich{Ward theory of upper bounds on the norm...

A method for the detection of fault lines of a surface only known at scattered data is presented. In particular, we use a technique for the detection of fault points, picking out and collecting in a set all the data points close to fault lines. To select these points we use a cardinal radial basis interpolation formula. Then, applying a powerful refinement technique, we discuss different method...

A fast multipole method (FMM) for asymptotically smooth kernel functions (1/r, 1/r4, Gauss and Stokes kernels, radial basis functions, etc.) based on a Chebyshev interpolation scheme has been introduced in [5]. The method has been extended to oscillatory kernels (e.g., Helmholtz kernel) in [12]. Beside its generality this FMM turns out to be favorable due to its easy implementation and its high...

This paper deals with some basic aspects of scattered data problems. In particular, the following topics are discussed: Self-adjoint scattered data interpolation, sampling sets and interpolation sets, and irregular sampling of shift-invariant spline spaces. Results on band-limited functions are presented as well as results on univariate splines on the real line. x0. Introduction Scattered data ...