A cognitive neural linearization model design for temperature measurement system based on optimization algorithm
Author
Source
Iraqi Journal of Computer, Communications and Control Engineering
Issue
Vol. 15, Issue 1 (30 Apr. 2015), pp.61-71, 11 p.
Publisher
Publication Date
2015-04-30
Country of Publication
Iraq
No. of Pages
11
Main Subjects
Topics
Abstract EN
The main core of this paper is to design an experimental method for estimating of the nonlinearity, calibrating and testing of the different types of thermocouples temperature sensors (J, K, T, S and R) using multi-layer perceptron (MLP) neural network based on slice genetic (SG) optimization learning algorithm.
Temperature sensor has a nonlinearity behavior nature in its output response but it requires a linear behavior output with accepts approximation in accuracy level, noise and measurement errors.
Therefore, neural network topology is proposed with five main steps algorithm to reduce the effected noise and minimize the measured errors.
Matlab simulation results and laboratory work (LabVIEW) validate the preciously of the proposed cognitive neural linearization algorithm in terms of calculating the temperature from the different types of thermocouples temperature sensors and minimizing the error between the actual temperature output and neural linearization temperature output as well as overcoming the problem of the over learning in the linearization model with the minimum number of fitness evaluation for the learning algorithm..
American Psychological Association (APA)
Abd al-Ahad, Haydar. 2015. A cognitive neural linearization model design for temperature measurement system based on optimization algorithm. Iraqi Journal of Computer, Communications and Control Engineering،Vol. 15, no. 1, pp.61-71.
https://search.emarefa.net/detail/BIM-582933
Modern Language Association (MLA)
Abd al-Ahad, Haydar. A cognitive neural linearization model design for temperature measurement system based on optimization algorithm. Iraqi Journal of Computer, Communications and Control Engineering Vol. 15, no. 1 (2015), pp.61-71.
https://search.emarefa.net/detail/BIM-582933
American Medical Association (AMA)
Abd al-Ahad, Haydar. A cognitive neural linearization model design for temperature measurement system based on optimization algorithm. Iraqi Journal of Computer, Communications and Control Engineering. 2015. Vol. 15, no. 1, pp.61-71.
https://search.emarefa.net/detail/BIM-582933
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 71
Record ID
BIM-582933