Purposeful model parameters genesis in simple genetic algorithms

Optimizing configurable parameters of model structure using genetic algorithms

Fractionation product properties of crude distillation unit (CDU) need to be monitored and controlled through feedback mechanism. Due to inability of on-line measurement, soft sensors for product quality estimation are developed. Soft sensors for kerosene distillation end point are developed using linear and nonlinear identification methods. Experimental data are acquired from the refinery dist...

Evolving Parameters of Logit Model Using Genetic Algorithms

Extraction of Process Model Parameters Based on Distributed Genetic Algorithms

In this paper, we present a GA (Genetic Algorithm) application for process model calibration. We propose a distributed GA-based calibration technique combined with the traditional local optimization algorithm, which reduces calibration time considerably. Experimental results on a PC cluster system (eight PCs) demonstrate that the calibration of 144 parameters can be completed within a few minut...

Hyperplane Ranking in Simple Genetic Algorithms

We examine the role of hyperplane ranking during genetic search by developing a metric for measuring the degree of ranking that exists with respect to static hyperplane averages taken directly from the function, as well as the dynamic ranking of hyperplanes during genetic search. The metric applied to static rankings subsumes the concept of deception but the metric provides a more precise chara...

Self-adaptive parameters in genetic algorithms

Genetic algorithms are powerful search algorithms that can be applied to a wide range of problems. Generally, parameter setting is accomplished prior to running a Genetic Algorithm (GA) and this setting remains unchanged during execution. The problem of interest to us here is the self-adaptive parameters adjustment of a GA. In this research, we propose an approach in which the control of a gene...