A python implementation of the algorithm used to generate optimal piecewise linear approximations of convex functions proposed by Imamoto and Tang [1]. The algorithm uses an iterative search to find ...
Abstract: This paper proposes a method for calculating the economic generation dispatch for generating units with a piecewise linear incremental cost function, at the same time considering total power ...
This is a preview. Log in through your library . Abstract The modeling of traffic control systems for solving such problems as surface street signalization, dynamic traffic assignment, etc., typically ...
PiecewiseLinearOpt.jl is a JuMP extension for modeling optimization problems containing piecewise linear functions. This package is an accompaniment to a paper entitled Nonconvex piecewise linear ...
Abstract: Piecewise-linear (PWL) functions are frequently used to describe the nonlinear branch equations of nonlinear devices in LSI circuits. New techniques for the solution of the differential ...
This is a preview. Log in through your library . Mathematics of Operations Research publishes articles concerned with mathematical and computational foundations of operations research, including ...
The mathematical foundation of deep learning is the theorem that any continuous function can be approximated within any specified accuracy by using a neural network with certain non-linear activation ...
ABSTRACT: In this paper, we propose a method for finding the best piecewise linearization of nonlinear functions. For this aim, we try to obtain the best approximation of a nonlinear function as a ...
It’s been suggested by various wits that the most widely used application of Mathematica is cheating on calculus homework. Actually, Mathematica does most of the heavy lifting in physics, applied math ...
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