Novel approach for predicting direct and open solar drying using artificial neural network for medicinal plant
In this study, an artificial neural network (ANN) was developed to obtain a generalized model for predicting the direct and open sun drying process for some medicinal plants. Since the quality of the experimental dataset can lead to a very performant model, in this study the dataset was collected fr...
| Permalink: | http://skupnikatalog.nsk.hr/Record/nsk.NSK01001144967/Details |
|---|---|
| Matična publikacija: |
Kemija u industriji (Online) 70 (2021), 3/4 ; str. 145-152 |
| 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.2020.049 Kemija u industriji (Online) Hrčak |
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| 080 | 1 | |a 66 |2 2011 | |
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| 100 | 1 | |a Sadadou, Ahmed |4 aut |9 HR-ZaNSK | |
| 245 | 1 | 0 | |a Novel approach for predicting direct and open solar drying using artificial neural network for medicinal plant |h [Elektronička građa] / |c Ahmed Sadadou, Salah Hanini, Maamar Laidi, Ahmed Rezrazi. |
| 300 | |b Graf. prikazi. | ||
| 504 | |a Bibliografija: 29 jed. | ||
| 504 | |a Abstract ; Sažetak. | ||
| 520 | |a In this study, an artificial neural network (ANN) was developed to obtain a generalized model for predicting the direct and open sun drying process for some medicinal plants. Since the quality of the experimental dataset can lead to a very performant model, in this study the dataset was collected from previously published papers and divided randomly into three subsets, namely 70 %, 15 %, and 15 % for training, testing, and validation. Based on the complex solar drying behaviour, ten parameters were considered as inputs: time, global solar radiation (GSR), outside temperature, inclination, emissivity, altitude, longitude, latitude, inside temperature, and nutritional value, to predict moisture content (MC), and drying rate (DR). Based on a trial and error method, the best ANN model was found with a topology of 10-28-14-2, with regression coefficient and root mean square error of (R = 97.044 %. RMSE = 4.589 %) and (R = 99.968 %, RMSE = 1.185 %) for MC and DR, respectively. It can be concluded that the obtained ANN model provides the best method for solar dryer modelling which can be generalized for any location in the world. | ||
| 520 | |a U ovom istraživanju razvijena je umjetna neuronska mreža (ANN) za dobivanje uopćenog modela za predviđanje izravnog i otvorenog postupka solarnog sušenja za određene ljekovite biljke. Budući da kvaliteta eksperimentalnog skupa podataka može dovesti do modela visoke izvedbe, u ovoj je studiji skup podataka prikupljen iz prethodno objavljenih radova i nasumce podijeljen u tri podskupine – 70 % za trening, 15 % za testiranje i 15 % za validaciju. Na temelju složenog postupka solarnog sušenja, za predviđanje sadržaja vlage (SV) i brzine sušenja (BS) uzima se deset ulaznih parametara: vrijeme, globalno sunčevo zračenje (GSZ), vanjska temperatura, nagib, emisivnost, nadmorska visina, zemljopisna dužina, zemljopisna širina, unutarnja temperatura i hranjiva vrijednost. Na temelju metode pokušaja i pogreške, pronađen je najbolji model ANN s topologijom 10-28-14-2 te koeficijentom regresije i srednjom kvadratnom pogreškom od (R = 97,044 %, RMSE = 4,589 %) za SV i (R = 99,968 %, RMSE = 1,185 %) za BS. Može se zaključiti da je dobiveni ANN najbolji model za modeliranje solarnih sušilica koji se može generalizirati za bilo koje mjesto na svijetu. | ||
| 653 | 0 | |a Umjetne neuronske mreže |a Ljekovite biljke |a Solarno sušenje |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), 3/4 ; str. 145-152 |w nsk.(HR-ZaNSK)000530475 | |
| 981 | |b Be2021 |b B03/21 | ||
| 998 | |b tino2212 | ||
| 856 | 4 | 0 | |u https://doi.org/10.15255/KUI.2020.049 |
| 856 | 4 | 0 | |u http://silverstripe.fkit.hr/kui/issue-archive/article/787 |y Kemija u industriji (Online) |
| 856 | 4 | 1 | |y Digitalna.nsk.hr |
| 856 | 4 | 0 | |u https://hrcak.srce.hr/254683 |y Hrčak |