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Information Journal Paper

Title

SOLVING INTEGRO-DIFFERENTIAL EQUATION BY USING B- SPLINE INTERPOLATION

Pages

  237-244

Abstract

 Abstract. In this paper, we introduce a hybrid approach based on MODIFIED NEURAL NETWORKS and optimization teqnique to solve ordinary differential equation. Using modified neural net- work makes that training points should be selected over the  open interval (a, b) without training the network in the range of first and end points. Therefore, the calculating volume involving computational error is reduced. In fact, the training points depending on the distance [a, b] selected for training neural networks are converted to similar points in the open interval (a, b) by using a new approach, then the network is trained in these similar areas. In comparison with existing similar neural networks proposed model provides solutions with high accuracy. Numerical examples with simulation results illustrate the effectiveness of the proposed model.

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    Cite

    APA: Copy

    AMIRFAKHRIAN, M., & SHAKIBIA, K.. (2013). SOLVING INTEGRO-DIFFERENTIAL EQUATION BY USING B- SPLINE INTERPOLATION. INTERNATIONAL JOURNAL OF MATHEMATICAL MODELLING & COMPUTATION, 3(3), 237-244. SID. https://sid.ir/paper/328287/en

    Vancouver: Copy

    AMIRFAKHRIAN M., SHAKIBIA K.. SOLVING INTEGRO-DIFFERENTIAL EQUATION BY USING B- SPLINE INTERPOLATION. INTERNATIONAL JOURNAL OF MATHEMATICAL MODELLING & COMPUTATION[Internet]. 2013;3(3):237-244. Available from: https://sid.ir/paper/328287/en

    IEEE: Copy

    M. AMIRFAKHRIAN, and K. SHAKIBIA, “SOLVING INTEGRO-DIFFERENTIAL EQUATION BY USING B- SPLINE INTERPOLATION,” INTERNATIONAL JOURNAL OF MATHEMATICAL MODELLING & COMPUTATION, vol. 3, no. 3, pp. 237–244, 2013, [Online]. Available: https://sid.ir/paper/328287/en

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