Technologies of intellectual analysis of the data in agricultural research

DOI

10.2991/ispc-19.2019.71How to use a DOI?

Keywords

digital economy, agricultural research, data mining, multiple comparison of means, multivariate analysis of variance

Abstract

An important factor in increasing the efficiency of decisions made on the results of agricultural research is the use of advanced digital economy technologies. However, in practice, the analysis of empirical results is often limited to a pairwise comparison of means on impact options, without taking into account the realities of the plan of laboratory or field experiments. The possibility of obtaining new knowledge using information technologies for the analysis of empirical data that support algorithms for multiple comparison of means and multivariate analysis of variance is discussed. To implement these algorithms, you do not need to access expensive software products of the Data Mining class (DM); it is enough to have relatively inexpensive statistical data analysis packages such as early versions of SPSS (Statistical Package for the Social Sciences) starting from version 8.0. An example is given to illustrate the effectiveness of using information systems of the Knowledge Discovery class, focused on the data knowledge search.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Viktor Buyarov
AU  - Vadim Shumetov
AU  - Aleksandr Buyarov
AU  - Yulia Mikhaylova
PY  - 2019/06
DA  - 2019/06
TI  - Technologies of intellectual analysis of the data in agricultural research
BT  - Proceedings of the International Scientific and Practical Conference “Digital agriculture - development strategy” (ISPC 2019)
PB  - Atlantis Press
SP  - 315
EP  - 318
SN  - 1951-6851
UR  - https://doi.org/10.2991/ispc-19.2019.71
DO  - 10.2991/ispc-19.2019.71
ID  - Buyarov2019/06
ER  -