PERFORMANCE OF THE SOLAR DRYER AND MOISTURE CONTENT PREDICTION OF SWEET TAMARIND USING AN ANN

Authors

  • Jagrapan Piwsaoad Faculty of Education, Loei Rajabhat Univercity
  • Chayapat Phusumpao Faculty of Education, Loei Rajabhat University

DOI:

https://doi.org/10.14456/lsej.2023.22

Keywords:

Solar dryer, Artificial neural network modeling , Sweet tamarind

Abstract

This research presents the experimental performance of solar dryers and artificial neural network modeling of solar dryers for drying sweet tamarinds. Fifteen batches of sweet tamarinds were drying; for each batch, we used 2.0 kilograms of sweet tamarinds. The parameters used in the artificial neural network model are solar radiation, air temperature, relative humidity and airflow rate. The numerical solution was programmed in C++. The results showed that the moisture content, calculated from the model corresponds to the measured values RMSE=0.5013 and R2=0.9818.

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Published

2023-09-01

How to Cite

Piwsaoad, J., & Phusumpao, C. . (2023). PERFORMANCE OF THE SOLAR DRYER AND MOISTURE CONTENT PREDICTION OF SWEET TAMARIND USING AN ANN. Life Sciences and Environment Journal, 24(2), 285–296. https://doi.org/10.14456/lsej.2023.22

Issue

Vol. 24 No. 2 (2023): July - December

Section

Research Articles

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Copyright (c) 2023 Life Sciences and Environment Journal

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