| Issue |
E3S Web Conf.
Volume 224, 2020
Topical Problems of Agriculture, Civil and Environmental Engineering (TPACEE 2020)
|
|
|---|---|---|
| Article Number | 01021 | |
| Number of page(s) | 5 | |
| Section | Mathematical Models for Environmental Monitoring and Assessment | |
| DOI | https://doi.org/10.1051/e3sconf/202022401021 | |
| Published online | 23 December 2020 | |
Using a Boolean derivative to evaluate the significance of properties of recognized objects
Institute of Applied Mathematics and Automation KBSC RAS (IAMA KBSC RAS), 89a, str. Shortanova, 360000, KBR, Nalchik, Russia
* Corresponding author: lylarisa@yandex.ru
This paper offers an approach for evaluating the significance of individual characteristics of recognized objects. The scope of this approach is not the subject area where objects and characteristics of these objects are specified, but a trained ∑Π - neural network that works correctly on the specified subject area. In this paper, we propose a method for constructing a crucial function based on the weight characteristics of a correctly functioning ∑Π - neuron. A logical derivative is used to evaluate the significance of object characteristics. This makes it possible to track how the decision function will change its value if one or more object characteristics change their value. This will allow us to draw a conclusion about the most important properties of the subject area under consideration.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.