Inductive Databases of Polynomial Equations

A Generalization of the Least General Generalization HirokiArimura,

In this chapter, we present a polynomial time algorithm, called a k-minimal multiple generalization (k-mmg) algorithm, where k 1, and its application to inductive learning problems. The algorithm is a natural extension of the least general generalization algorithm developed by Plotkin and Reynolds. Given a nite set of ground rst-order terms, the k-mmg algorithm generalizes the examples by at mo...

Canonical representation for approximating solution of fuzzy polynomial equations

In this paper, the concept of canonical representation is proposed to find fuzzy roots of fuzzy polynomial equations. We transform fuzzy polynomial equations to system of crisp polynomial equations, this transformation is perform by using canonical representation based on three parameters Value, Ambiguity and Fuzziness. 

Numerical solution of a system of fuzzy polynomial equations by modified Adomian decomposition method

In this paper, we present some efficient numerical algorithm for solving system of fuzzy polynomial equations based on Newton's method. The modified Adomian decomposition method is applied to construct the numerical algorithms. Some numerical illustrations are given to show the efficiency of algorithms.

Non-polynomial Spline Method for Solving Coupled Burgers Equations

In this paper, non-polynomial spline method for solving Coupled Burgers Equations are presented. We take a new spline function. The stability analysis using Von-Neumann technique shows the scheme is unconditionally stable. To test accuracy the error norms 2L, L are computed and give two examples to illustrate the sufficiency of the method for solving such nonlinear partial differential equation...

A New Approach to the Numerical Solution of Dual Fully Fuzzy Polynomial Equations