دانلود مقاله انگلیسی رایگان:پیش بینی جابجایی در استخوان metacarpal سوم اسب با استفاده از الگوریتم پیش بینی شبکه عصبی - 2019
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  • Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm
    Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm

    سال انتشار:

    2019


    عنوان انگلیسی مقاله:

    Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm


    ترجمه فارسی عنوان مقاله:

    پیش بینی جابجایی در استخوان metacarpal سوم اسب با استفاده از الگوریتم پیش بینی شبکه عصبی


    منبع:

    Sciencedirect - Elsevier - Integrative Medicine Research, Corrected proof: doi:10:1016/j:bbe:2019:09:001


    نویسنده:

    Saeed Mouloodi a,b,*, Hadi Rahmanpanah c, Colin Burvill a, Helen MS Davies


    چکیده انگلیسی:

    Bone is a nonlinear, inhomogeneous and anisotropic material. To predict the behavior of bones expert systems are employed to reduce the computational cost and to enhance the accuracy of simulations. In this study, an artificial neural network (ANN) was used for the prediction of displacement in long bones followed by ex-vivo experiments. Three hydrated third metacarpal bones (MC3) from 3 thoroughbred horses were used in the experiments. A set of strain gauges were distributed around the midshaft of the bones. These bones were then loaded in compression in an MTS machine. The recordings of strains, load, Load exposure time, and displacement were used as ANN input parameters. The ANN which was trained using 3,250 experimental data points from two bones predicted the displacement of the third bone (R2 ≥ 0.98). It was suggested that the ANN should be trained using noisy data points. The proposed modification in the training algorithm makes the ANN very robust against noisy inputs measurements. The performance of the ANN was evaluated in response to changes in the number of input data points and then by assuming a lack of strain data. A finite element analysis (FEA) was conducted to replicate one cycle of force-displacement experimental data (to gain the same accuracy produced by the ANN). The comparison of FEA and ANN displacement predictions indicates that the ANN produced a satisfactory outcome within a couple of seconds, while FEA required more than 160 times as long to solve the same model (CPU time: 5 h and 30 min).
    Keywords: Artificial neural network (ANN) | Displacement prediction | Finite element analysis (FEA) | Expert system | Long bones | Equine third metacarpal bone (MC3)


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 15
    حجم فایل: 4262 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




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