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arXiv 1904.096562019-04-21cs.LGcs.NAmath.NA

使用功能链接人工神经网络求解定积分

Solution of Definite Integrals using Functional Link Artificial Neural Networks

Department of Information Technology, Institute of Engineering and Management（信息科技系，工程管理学院）

Satyasaran Changdar, Snehangshu Bhattacharjee

备注：: 14 pages, 7 figures

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AI总结：

本文提出了一种利用人工神经网络求解定积分的新方法，通过最小化精心设计的误差函数，构建出一种新颖的替代传统数值方法的神经网络，特别适用于高阶多项式积分。

摘要：

本文讨论了一种利用人工神经网络求解定积分的新方法。目的是构建一个神经网络，作为传统数值方法的新替代方案，并通过学习算法能够求解定积分，通过最小化精心设计的误差函数。所提出的算法与现有数值方法相比更为有效和精确，适用于需要积分高阶多项式的场合。观察结果以表格和图形形式记录并展示。

英文摘要：

This paper discusses a new method to solve definite integrals using artificial neural networks. The objective is to build a neural network that would be a novel alternative to pre-established numerical methods and with the help of a learning algorithm, be able to solve definite integrals, by minimising a well constructed error function. The proposed algorithm, with respect to existing numerical methods, is effective and precise and well-suited for purposes which require integration of higher order polynomials. The observations have been recorded and illustrated in tabular and graphical form.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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