Some Features of Intelligent Analysis of Empirical Data Collections Updated with New Information, but Limited in Size

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-09-01 DOI:10.3103/S0005105523030093
M. I. Zabezhailo, A. V. Amentes
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Abstract

This paper discusses certain possibilities and limitations of the use of mathematical models and methods of computer data analysis in the processing of collections of empirical data, which are open, replenished with new elements but limited in size. The characteristics of the statistical methods of data analysis, artificial neural networks, and methods based on interpolation-extrapolation techniques for identifying empirical cause-and-effect dependencies hidden in the analyzed data are considered.

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用新信息更新但规模有限的经验数据集的智能分析的一些特征
本文讨论了在处理经验数据集时使用数学模型和计算机数据分析方法的某些可能性和局限性,这些数据集是开放的,补充了新的元素,但规模有限。考虑了数据分析的统计方法、人工神经网络和基于插值-外推技术的方法的特点,这些方法用于识别隐藏在分析数据中的经验因果相关性。
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来源期刊
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
18
期刊介绍: Automatic Documentation and Mathematical Linguistics  is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.
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