دانلود مقاله انگلیسی رایگان:پیش بینی دمای زمین با شبکه های عصبی، LS-SVM و LS-SVM فازی برای استفاده GSHP - 2020
بلافاصله پس از پرداخت دانلود کنید
دانلود مقاله انگلیسی داده های بزرگ رایگان
  • Prediction of the ground temperature with ANN, LS-SVM and fuzzy LS-SVM for GSHP application Prediction of the ground temperature with ANN, LS-SVM and fuzzy LS-SVM for GSHP application
    Prediction of the ground temperature with ANN, LS-SVM and fuzzy LS-SVM for GSHP application

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Prediction of the ground temperature with ANN, LS-SVM and fuzzy LS-SVM for GSHP application


    ترجمه فارسی عنوان مقاله:

    پیش بینی دمای زمین با شبکه های عصبی، LS-SVM و LS-SVM فازی برای استفاده GSHP


    منبع:

    Sciencedirect - Elsevier - Geothermics, 84 (2020) 101757: doi:10:1016/j:geothermics:2019:101757


    نویسنده:

    Shiyu Zhoua,*, Xin Chub, Shubo Caob, Xiaoping Liub, Yucheng Zhoub


    چکیده انگلیسی:

    Ground source heat pump (GSHP) system has received more and more attentions for its energy-conserving and environmental-friendly properties. Acquisition of the undisturbed ground temperature is the prerequisite for designing of GSHP system. Measurement by burying temperature sensors underground is the conventional means for obtaining the ground temperature data. However, this way is usually time consuming and high investment, and also easily encounter with certain technical difficulties. The rapid development of intelligent computation algorithm provides solutions for many realistic difficult problems. Basing on a great number of the measured data of the ground temperature from two boreholes with 100m depth located in Chongqing, ground temperature prediction models basing on artificial neural network (ANN) and support vector machine based on least square (LS-SVM) are established, respectively. And then, two kinds of validation works, i.e., holdout validation and k-fold validation are conducted toward the two models, respectively. Furthermore, a new method that correlating fuzzy theory with LS-SVM is proposed to solve the big computation burden problem encountered by LS-SVM model. By comparing with the above two models, it is concluded that the newly proposed model can not only improve the calculation speed obviously but also be able to promote the prediction accuracy, especially superior to the single LS-SVM model.
    Keywords: Ground temperature | Fuzzy | Support vector machine | Ground source heat pump


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 11
    حجم فایل: 2673 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




اگر این مقاله را پسندیدید آن را در شبکه های اجتماعی به اشتراک بگذارید (برای به اشتراک گذاری بر روی ایکن های زیر کلیک کنید)

تعداد نظرات : 0

الزامی
الزامی
الزامی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi