ANN-based approach to model MC/DR of some fruits under solar drying
The aim of this work was to model the moisture content (MC) and drying rate (DR) using artificial neural network (ANN) methodology. Many architectures have been tested and the best topology was selected based on a trial and error method. The dataset was randomly divided into 60, 20, and 20 % for tra...
| Permalink: | http://skupnikatalog.nsk.hr/Record/nsk.NSK01001144962/Details |
|---|---|
| Matična publikacija: |
Kemija u industriji (Online) 70 (2021), 5/6 ; str. 233-242 |
| Glavni autori: | Sadadou, Ahmed (Author), Hanini, Salah, Laidi, Maamar, Rezrazi, Ahmed |
| Vrsta građe: | e-članak |
| Jezik: | eng |
| Predmet: | |
| Online pristup: |
https://doi.org/10.15255/KUI.2020.050 Kemija u industriji (Online) Hrčak |
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| 008 | 220803s2021 ci d |o |0|| ||eng | ||
| 024 | 7 | |2 doi |a 10.15255/KUI.2020.050 | |
| 035 | |a (HR-ZaNSK)001144962 | ||
| 040 | |a HR-ZaNSK |b hrv |c HR-ZaNSK |e ppiak | ||
| 041 | 0 | |a eng |b hrv | |
| 042 | |a croatica | ||
| 044 | |a ci |c hr | ||
| 080 | 1 | |a 66 |2 2011 | |
| 080 | 1 | |a 004 |2 2011 | |
| 100 | 1 | |a Sadadou, Ahmed |4 aut |9 HR-ZaNSK | |
| 245 | 1 | 0 | |a ANN-based approach to model MC/DR of some fruits under solar drying |h [Elektronička građa] / |c Ahmed Sadadou, Salah Hanini, Maamar Laidi, Ahmed Rezrazi. |
| 246 | 3 | |a Artificial neural network -based approach | |
| 300 | |b Graf. prikazi. | ||
| 504 | |a Bibliografija: 44 jed. | ||
| 504 | |a Abstract ; Sažetak. | ||
| 520 | |a The aim of this work was to model the moisture content (MC) and drying rate (DR) using artificial neural network (ANN) methodology. Many architectures have been tested and the best topology was selected based on a trial and error method. The dataset was randomly divided into 60, 20, and 20 % for training, test, and validation stage of the ANN model, respectively. The best topology was 10-{29-13}-2 obtained with high correlation coefficient R (%) of {99.98, 98.41} and low root mean square error RMSE (%) (0.36, 6.29) for MC and DR, respectively. The obtained ANN can be used to interpolate the MC and DR with high accuracy. | ||
| 520 | |a Cilj ovog rada bio je modelirati sadržaj vlage (MC) i brzinu sušenja (DR) primjenom metodologije umjetne neuronske mreže (ANN). Testirane su mnoge arhitekture, a najbolja topologija odabrana je na temelju metode pokušaja i pogrešaka. Skup podataka podijeljen je nasumično na 60, 20 i 20 % za fazu treninga, testa i validacije ANN modela. Najbolja topologija bila je 10-{29-13}-2 dobivena visokim koeficijentom korelacije R (%) od {99,98, 98,41} i niskom srednjom kvadratnom pogreškom RMSE (%) (0,36, 6,29) za MC, odnosno DR. Dobiveni ANN model može se s velikom točnošću primijeniti za interpolaciju MC-a i DR-a. | ||
| 653 | 0 | |a Umjetne neuronske mreže |a Solarno sušenje |a Voće |a Sadržaj vlage |a Brzina sušenja | |
| 700 | 1 | |a Hanini, Salah |4 aut |9 HR-ZaNSK | |
| 700 | 1 | |a Laidi, Maamar |4 aut |9 HR-ZaNSK | |
| 700 | 1 | |a Rezrazi, Ahmed |4 aut |9 HR-ZaNSK | |
| 773 | 0 | |t Kemija u industriji (Online) |x 1334-9090 |g 70 (2021), 5/6 ; str. 233-242 |w nsk.(HR-ZaNSK)000530475 | |
| 981 | |b Be2021 |b B03/21 | ||
| 998 | |b tino2212 | ||
| 856 | 4 | 0 | |u https://doi.org/10.15255/KUI.2020.050 |
| 856 | 4 | 0 | |u http://silverstripe.fkit.hr/kui/issue-archive/article/788 |y Kemija u industriji (Online) |
| 856 | 4 | 1 | |y Digitalna.nsk.hr |
| 856 | 4 | 0 | |u https://hrcak.srce.hr/257538 |y Hrčak |