Conţinutul numărului revistei |
Articolul precedent |
Articolul urmator |
![]() |
![]() ![]() |
Ultima descărcare din IBN: 2019-11-21 00:12 |
Căutarea după subiecte similare conform CZU |
[634.7+663.26]:519.6:004.8 (1) |
Small fruits of shrubs and herbaceous plants. Berries (60) |
Wine. Winemaking. Oenology (268) |
Computational mathematics. Numerical analysis (91) |
Artificial intelligence (147) |
![]() GHENDOV-MOŞANU, Aliona; STURZA, Rodica; CHERECHEŞ, Tudor; PATRAȘ, Antoanela. A fuzzy logic approach for mathematical modeling of the extraction process of bioactive compounds. In: Journal of Engineering Sciences. 2019, nr. 3, pp. 89-99. ISSN 2587-3474. 10.5281/zenodo.3444119 |
EXPORT metadate: Google Scholar Crossref CERIF DataCite Dublin Core |
Journal of Engineering Sciences | |||||
Numărul 3 / 2019 / ISSN 2587-3474 /ISSNe 2587-3482 | |||||
|
|||||
CZU: [634.7+663.26]:519.6:004.8 | |||||
DOI: 10.5281/zenodo.3444119 | |||||
Pag. 89-99 | |||||
|
|||||
![]() |
|||||
Rezumat | |||||
The aim of the present study was to optimize the extraction process of bioactive compounds from berries and wastes from the agro-food industry (grape marc). Mathematical models of the extraction process of biologically active compounds based on algorithms of artificial intelligence: fuzzy logic and neuro-fuzzy algorithms have been established. The mathematical models, which use the experimental average values of uncertain models, as well as of some predictive models, offer values of the sizes with a large prediction horizon. It was established, that mathematical models, which use the experimental average values of uncertain models, the experimental data, as well as of some predictive models offer values of the sizes with a large prediction horizon. The existence of various interactions between the influence factors (ethanol concentration, extraction temperature, pretreatment method) and the measured parameters (total polyphenol index, quantity of tannins extracted and antiradical activity, DPPH) was established. The great diversity of processes at different products and various parameters, as well as the existence of non-linear dependencies between sizes, allow credible extrapolations of the results only within the experimental limits. |
|||||
Cuvinte-cheie fuzzy mathematical model, neuro-fuzzy mathematical model, Berries, extraction, bioactive compounds, model matematic fuzzy, model matematic neuro-fuzzy, extracţie, fructe de pădure, compuşi bioactivi |
|||||
|
DataCite XML Export
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns='http://datacite.org/schema/kernel-3' xsi:schemaLocation='http://datacite.org/schema/kernel-3 http://schema.datacite.org/meta/kernel-3/metadata.xsd'> <identifier identifierType='DOI'>10.5281/zenodo.3444119</identifier> <creators> <creator> <creatorName>Ghendov-Moşanu, A.</creatorName> <affiliation>Universitatea Tehnică a Moldovei, Moldova, Republica</affiliation> </creator> <creator> <creatorName>Sturza, R.A.</creatorName> <affiliation>Universitatea Tehnică a Moldovei, Moldova, Republica</affiliation> </creator> <creator> <creatorName>Cherecheş, T.</creatorName> <affiliation>UPS PILOT ARM LTD, România</affiliation> </creator> <creator> <creatorName>Patraș, A.</creatorName> <affiliation>Universitatea de Ştiinţe Agricole şi Medicină Veterinară „Ion Ionescu de la Brad”, Iaşi, România</affiliation> </creator> </creators> <titles> <title xml:lang='en'><p>A fuzzy logic approach for mathematical modeling of the extraction process of bioactive compounds</p></title> </titles> <publisher>Instrumentul Bibliometric National</publisher> <publicationYear>2019</publicationYear> <relatedIdentifier relatedIdentifierType='ISSN' relationType='IsPartOf'>2587-3474</relatedIdentifier> <subjects> <subject>fuzzy mathematical model</subject> <subject>neuro-fuzzy mathematical model</subject> <subject>Berries</subject> <subject>extraction</subject> <subject>bioactive compounds</subject> <subject>model matematic fuzzy</subject> <subject>model matematic neuro-fuzzy</subject> <subject>extracţie</subject> <subject>fructe de pădure</subject> <subject>compuşi bioactivi</subject> <subject schemeURI='http://udcdata.info/' subjectScheme='UDC'>[634.7+663.26]:519.6:004.8</subject> </subjects> <dates> <date dateType='Issued'>2019-11-10</date> </dates> <resourceType resourceTypeGeneral='Text'>Journal article</resourceType> <descriptions> <description xml:lang='en' descriptionType='Abstract'><p>The aim of the present study was to optimize the extraction process of bioactive compounds from berries and wastes from the agro-food industry (grape marc). Mathematical models of the extraction process of biologically active compounds based on algorithms of artificial intelligence: fuzzy logic and neuro-fuzzy algorithms have been established. The mathematical models, which use the experimental average values of uncertain models, as well as of some predictive models, offer values of the sizes with a large prediction horizon. It was established, that mathematical models, which use the experimental average values of uncertain models, the experimental data, as well as of some predictive models offer values of the sizes with a large prediction horizon. The existence of various interactions between the influence factors (ethanol concentration, extraction temperature, pretreatment method) and the measured parameters (total polyphenol index, quantity of tannins extracted and antiradical activity, DPPH) was established. The great diversity of processes at different products and various parameters, as well as the existence of non-linear dependencies between sizes, allow credible extrapolations of the results only within the experimental limits.</p></description> <description xml:lang='ro' descriptionType='Abstract'><p>Obiectivul studiului a constat în optimizarea procesului de extracţie a compușilor bioactivi din fructe de pădure și deșeuri din industria agroalimentară (tescovină de struguri). Au fost stabilite modele matematice ale procesului de extracţie a compușilor biologic activi, bazate pe algoritmi de inteligenţă artificială: logică fuzzy și algoritmi neuro-fuzzy. Modelele matematice, care folosesc valorile medii experimentale ale modelelor incerte, precum și ale unor modele predictive oferă valori ale mărimilor cu un orizont de predicţie mare. S-a stabilit existenţa diferitelor interacţii între factorii de influenţă (concentraţia de etanol, temperatura de extracţie, metoda de pretratare) și parametrii măsuraţi (indicele total de polifenol, cantitatea de tanin extras și activitatea antiradicalică, DPPH). Marea diversitate a proceselor la diferite produse și diverși parametri, precum şi existenţa unor dependenţe neliniare între mărimi permit extrapolări credibile ale rezultatelor doar în interiorul plajelor experimentale.</p></description> </descriptions> <formats> <format>application/pdf</format> </formats> </resource>