{
    "article_id": 424,
    "public_id": "ba0660b8-704e-4fd4-869d-8c98d7f6e7da",
    "internal_identifier": null,
    "source_identifier": "5:68",
    "status": "published",
    "type": "research_article",
    "title": "Güneş Enerjisi Destekli Kurutma Sistemi İle Elma Ürününün Kurutulması ve Kurutma Değerlerinin Yapay Sinir Ağı İle Modellenmesi",
    "title_secondary": null,
    "abstract": "Bu çalışmada güneş enerjisi destekli bir kurutma sistemi tasarlanarak elma kurutulmuştur. Kurutma deney verilerinden kuru baz nem içeriği (MCd), ayrılabilir nem oranı (MR),kurutma hızı (DR) ve konvektif ısı transfer katsayısı (hc) değerleri hesaplanmıştır. Açık havada güneş altında kurutma ile güneş enerjisi destekli kurutma sisteminde yapılan elma kurutma işleminin kurutma performansları karşılaştırılmıştır. Güneş enerjisi destekli kurutma sisteminde yapılan deney çalışmalarından elde edilen hc değerleri için yapay sinir ağı (YSA) kullanılarak tahminsel bir model oluşturulmuştur. Uygulanan YSA ile tahminsel hc değerleri gösterilmiştir. Elde edilen tahminsel modelin geçerliliğini belirlemek için, ortalama kareli hata (MSE), kök ortalama karesel hata (RMSE) ve bağıl mutlak hata (RAE) analizleri yapılmıştır. Sonuç olarak hc değerleri için tahminsel bir model elde edilmiştir ve güneş enerjisi destekli kurutma sistemi daha verimli bir kurutma gerçekleştirmiştir.  ",
    "language": "tr",
    "english_title": "Drying of Apple Product with a Solar Energy-Assisted Drying System and Modeling of Drying Values ​​Using Artificial Neural Networks",
    "english_abstract": "In this study, apples were dried using a solar energy-assisted drying system. Dry base moisture content (MCd), separable moisture content (MR), drying rate (DR), and convective heat transfer coefficient (hc) values ​​were calculated from the drying experimental data. The drying performance of apples dried in the open air under the sun and in a solar energy-assisted drying system was compared. A predictive model was created using an artificial neural network (ANN) for the hc values ​​obtained from the experiments in the solar energy-assisted drying system. The predicted hc values ​​obtained with the applied ANN are shown. To determine the validity of the obtained predictive model, mean squared error (MSE), root mean squared error (RMSE), and relative absolute error (RAE) analyses were performed. As a result, a predictive model for hc values ​​was obtained, and the solar energy-assisted drying system achieved more efficient drying.",
    "doi": null,
    "doi_url": null,
    "resource_url": "https://www.set-science.com/a/ba0660b8-704e-4fd4-869d-8c98d7f6e7da",
    "pdf_url": "https://www.set-science.com/a/ba0660b8-704e-4fd4-869d-8c98d7f6e7da/pdf",
    "og_image": "https://www.set-science.com/assets/img/og-card-v2.png",
    "authors": [
        {
            "public_id": "32d380ed-0195-4858-93da-8ba33e496bcc",
            "given": "Ahmet Doğukan ",
            "family": "Yazıcı",
            "full": "Ahmet Doğukan  Yazıcı",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "ahmet.yazici@erzincan.edu.tr",
            "corresponding": true,
            "sequence": "first",
            "affiliations": [
                {
                    "name": "Erzincan Üniversitesi, İliç Dursun Yıldırım Meslek Yüksekokulu",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        },
        {
            "public_id": "5ba4c2f0-227f-484f-9d9f-796fbceb76dd",
            "given": "Mehmet",
            "family": "Daş",
            "full": "Mehmet Daş",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "mdas@erzincan.edu.tr",
            "corresponding": false,
            "sequence": "additional",
            "affiliations": [
                {
                    "name": "Erzincan Üniversitesi, İliç Dursun Yıldırım Meslek Yüksekokulu, İklimlendirme ve Soğutma Teknolojisi Programı ",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        }
    ],
    "keywords": [],
    "translations": [
        {
            "language": "en",
            "title": "Drying of Apple Product with a Solar Energy-Assisted Drying System and Modeling of Drying Values ​​Using Artificial Neural Networks",
            "abstract": "In this study, apples were dried using a solar energy-assisted drying system. Dry base moisture content (MCd), separable moisture content (MR), drying rate (DR), and convective heat transfer coefficient (hc) values ​​were calculated from the drying experimental data. The drying performance of apples dried in the open air under the sun and in a solar energy-assisted drying system was compared. A predictive model was created using an artificial neural network (ANN) for the hc values ​​obtained from the experiments in the solar energy-assisted drying system. The predicted hc values ​​obtained with the applied ANN are shown. To determine the validity of the obtained predictive model, mean squared error (MSE), root mean squared error (RMSE), and relative absolute error (RAE) analyses were performed. As a result, a predictive model for hc values ​​was obtained, and the solar energy-assisted drying system achieved more efficient drying.",
            "keywords": [
                "Güneş Enerjisi, Kurutma, Yapay Sinir Ağı"
            ]
        }
    ],
    "subjects": [],
    "subject_names": [],
    "published_date": "2018-06-23",
    "published_year": "2018",
    "received_date": null,
    "accepted_date": null,
    "volume": "2",
    "issue": null,
    "page_first": "72",
    "page_last": "72",
    "article_number": null,
    "conference": {
        "short_name": "ISAS 2018",
        "full_title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "name": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "acronym": "ISAS 2018",
        "location": "Kemer-Antalya, Türkiye",
        "start_date": "2018-04-11",
        "end_date": null,
        "public_id": "1d94fec9-c4fe-4034-9157-0b205eef4e56"
    },
    "proceedings": {
        "title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "series_title": "Setsci conference indexing system",
        "publisher": "SET Technology",
        "isbn": null,
        "eisbn": null,
        "issn": "2618-6446",
        "eissn": null,
        "doi": null,
        "doi_prefix": null,
        "slug": "setsci-volume-2-2018-legacy-5",
        "public_id": "03da7b1c-cb6e-4f3b-aee4-ac41ee60fd75",
        "url": "https://www.set-science.com/p/setsci-volume-2-2018-legacy-5"
    },
    "license": {
        "name": "CC BY 4.0",
        "url": "https://creativecommons.org/licenses/by/4.0/",
        "code": "CC-BY-4.0",
        "open_access": true
    },
    "copyright": {
        "holder": "SET Technology",
        "year": "2018"
    },
    "funding_statement": null,
    "funders": [],
    "references": [],
    "statements": {
        "acknowledgements": null,
        "conflict_of_interest": null,
        "data_availability": null,
        "ai_disclosure": null
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    "credit": [],
    "history": {
        "published": "2018-06-23"
    }
}