SELF-HEATING PHENOMENON AND NONLINEAR CHARACTERISTIC MODELING OF NTC USING ARTIFICIAL NEURAL NETWORK FOR DIRECT MEASUREMENT OF TEMPERATURE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

GHASEMI JAMAL; MAHDIPOUR MOHAMMAD

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT) Year:2016 | Volume:6 | Issue:1 Page(s): 8-15

Download Full-Text

Persian Verion

View:

755

Download:

Cites:

Information Journal Paper

Title

SELF-HEATING PHENOMENON AND NONLINEAR CHARACTERISTIC MODELING OF NTC USING ARTIFICIAL NEURAL NETWORK FOR DIRECT MEASUREMENT OF TEMPERATURE

Author(s)

GHASEMI JAMAL | MAHDIPOUR MOHAMMAD | Issue Writer Certificate

Keywords

TEMPERATUREQ2

NTC SENSORQ2

SELF-HEATINGQ2

ARTIFICIAL NEURAL NETWORKQ1

Abstract

In the engineering systems, one of the most important measurable parameters is TEMPERATURE. For measurement of TEMPERATURE as for sensitivity, accuracy and term of physical required, different sensors as RTD, NTC, PTC, Thermo-couple are exist. One of the most important sensors is NTC that despite the many benefits, less than it used to be. Nonlinearity characteristic and SELF-HEATING phenomenon in the NTC are the biggest deterrents in practical applications. In this study, a new structure based on application of ARTIFICIAL NEURAL NETWORK (ANN) has been suggested for modeling of the nonlinear and the SELF-HEATING phenomenons of NTC. Simulation results based on read generated laboratory data are presented to demonstrate the performance of the proposed structure. Mean square error of 0.0480 and 0.0370 are achieved based on MLP and RBF neural network, respectively.

Cites

No record.

References

No record.

Cite

APA: Copy

GHASEMI, JAMAL, & MAHDIPOUR, MOHAMMAD. (2016). SELF-HEATING PHENOMENON AND NONLINEAR CHARACTERISTIC MODELING OF NTC USING ARTIFICIAL NEURAL NETWORK FOR DIRECT MEASUREMENT OF TEMPERATURE. JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT), 6(1 ), 8-15. SID. https://sid.ir/paper/245859/en

Vancouver: Copy

GHASEMI JAMAL, MAHDIPOUR MOHAMMAD. SELF-HEATING PHENOMENON AND NONLINEAR CHARACTERISTIC MODELING OF NTC USING ARTIFICIAL NEURAL NETWORK FOR DIRECT MEASUREMENT OF TEMPERATURE. JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT)[Internet]. 2016;6(1 ):8-15. Available from: https://sid.ir/paper/245859/en

IEEE: Copy

JAMAL GHASEMI, and MOHAMMAD MAHDIPOUR, “SELF-HEATING PHENOMENON AND NONLINEAR CHARACTERISTIC MODELING OF NTC USING ARTIFICIAL NEURAL NETWORK FOR DIRECT MEASUREMENT OF TEMPERATURE,” JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT), vol. 6, no. 1 , pp. 8–15, 2016, [Online]. Available: https://sid.ir/paper/245859/en

Related Journal Papers