A simple algorithm for solving a set of nonlinear equations by
matrix algebra has been discovered recently - first by transforming
them into an equivalent matrix equation and then finding the
solution analytically in terms of the inverse matrix of this
equation. With this newly developed ACORN (Adaptive Constrained
Optimal Robust Nonlinear) algorithm, it is possible to minimize the
objective function [constructed from the functions in the nonlinear
set of equations] without computing its derivatives.This book will
present the details of ACORN algorithm and how it is used to solve
large scale nonlinear equations with an innovative approach ACORN
Magic [minimization algorithms gathered in a cloud].The ultimate
motivation of this work is its application to optimization. In
recent years, with the advances in big-data, optimization becomes
an even more powerful tool in knowledge discovery. ACORN Magic is
the perfect choice in this kind of application because of that fact
that it is fast, robust and simple enough to be embedded in any
type of machine learning program.
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