本体方法在迭代GMDH算法元模型构建中的应用

H. Pidnebesna, Y. Savchenko-Synyakova, V. Stepashko
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引用次数: 1

摘要

提出构建迭代算法的本体元模型,以构建关于这些算法及其实现的知识。元模型将自动设计和使用专门的软件来解决特定的应用建模问题。迭代GMDH算法相对于组合算法的优势在于它们允许处理大数据集。已知的广义迭代算法,允许您在设置该算法的各种操作模式时,创建先前开发的这些算法修改的典型架构。作者已经开发了一个本体论元模型的迭代GMDH算法使用prot环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of the Ontological Approach to the Iterative GMDH Algorithms Metamodel Construction
Construction of an ontological metamodel of iterative algorithms is proposed to structure knowledge about these algorithms and their implementation. The metamodel will automate the design and use of specialized software for solving specific applied modeling problems. The advantage of iterative GMDH algorithms over combinatorial ones is that they allow the big datasets processing. The known generalized iterative algorithm, allows you to create typical architectures of previously developed modifications of these algorithms when setting up various modes of operation of this algorithm. The authors have developed an ontological metamodel of iterative GMDH algorithms using the Protégé environment.
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