Rice Bran Drying Kinetics of a Controlled Microwave Vacuum Dryer Optimized PLC-based: A Neuro-fuzzy Approach
| Autor: | Jayson P. Rogelio, Argel A. Bandala, Renann G. Baldovino, Elmer P. Dadios, Ryan Rhay P. Vicerra |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Adaptive neuro fuzzy inference system
Neuro-fuzzy Moisture Artificial neural network 020209 energy Word error rate Rotational speed 04 agricultural and veterinary sciences 02 engineering and technology 040401 food science Fuzzy logic 0404 agricultural biotechnology Control theory 0202 electrical engineering electronic engineering information engineering Microwave Mathematics |
| Zdroj: | 2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM). |
| Popis: | There have been several attempts to stabilize the rice bran using traditional physical, mathematical, and statistical methods for precise modeling but it is computationally laborious. In this study, the drying kinetics of the rice bran in prediction of the moisture loss was modelled through the neuro-fuzzy approach. The input parameters that were considered were microwave power, rotation speed, drying time, load capacity and vacuum pressure. A fuzzy inference system is designed to generate the rules of fuzzy logic where inputs of these are from the output of the trained neural network. Based on the result, it was found out that developed system was able to predict the moisture loss with error rate of 0.00014627. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|