Open AccessPossibilities for predicting the state of usability web resources
Author(s) -
Irina Astachova,
Katerina Makoviy,
Yu. Khitskova
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1902/1/012029
Subject(s) - autoregressive integrated moving average , usability , computer science , series (stratigraphy) , artificial neural network , time series , nonlinear autoregressive exogenous model , state (computer science) , data mining , artificial intelligence , machine learning , human–computer interaction , algorithm , paleontology , biology
The article discusses the possibilities of predicting the state of the web resources usability. The usability testing procedure is quite costly from both financial and time points of view. Therefore, a system that reduces these costs is useful for modern organizations. Different approaches of forecasting the number of visitors: ARIMA model and Neural Networks are considered. An important time series property for ARIMA model being applicable is the stationarity of the series. It is shown that this model is not suitable enough for the investigated time series, some types of neural networks are also not suitable for various reasons. As a result, NARX networks are selected, which are successfully used for time series forecasting, providing an opportunity to use an exogenous variable.