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Optimizing Discrete Modeling and Simulation for Real-Time Constraints with Metaprogramming
Published in Katalin Popovici, Pieter J. Mosterman, Real-Time Simulation Technologies, 2017
Luc Touraille, Jonathan Caux, David Hill
In mathematics and computer science, partial application is the technique of transforming a function with several parameters to another function with a smaller arity where some of the parameters have been fixed to a given value. Partial evaluation is quite similar, except that it applies to programs instead of mathematical functions. A partial evaluator is an algorithm that takes as input a source program and some of its inputs, and generates a residual or specialized program. When run with the rest of the inputs, the residual program generates the same output as the original program. However, in the meantime, the partial evaluator had the opportunity to evaluate every part of the original program that depended on the provided inputs. Consequently, the residual program performs fewer operations than the source program, hence exhibiting better performance. Formally, we consider a program as a function of static and dynamic data given as input, which produces some output:
Runway groove closure prediction modelling by gene expression programming (GEP)
Published in Road Materials and Pavement Design, 2023
Md Tofail Miah, Erwin Oh, Gary Chai, Phill Bell
GeneXproTools got numerous built-in mathematical functions (such as +, −, ×, /, x2, √3, ln, and exp) that allows users to develop custom functions to advance models with them. This extensive range of mathematical functions permits to fabrication of highly sophisticated and more precise models. The GEP models utilised seventeen functions as delineated in Table 5. Arity is the number of arguments used by the functions in the function set. The number of arguments it can be permitted to take is a minimum of 1 and a maximum of 4 by deciding the arity. However, the value of arity is chosen 1 and 2 for different symbolic functions during model configuration. By default, the weight of each function is considered 1. However, the probability of a function being included in the models can be augmented by increasing its weight, and a maximum weight of 6 was allocated for some functions.
An ASM-based characterisation of starvation-free systems
Published in International Journal of Parallel, Emergent and Distributed Systems, 2018
Alessandro Bianchi, Sebastiano Pizzutilo, Gennaro Vessio
Definition 1 (Signature). A signature Σ is a finite collection of function names. Each function is characterised by an arity which is the number of arguments that function takes. Every signature is assumed to contain the constants true, false and undef.