Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/75312
Title: Using the multilayer neural network for tasks of updating the user interface
Authors: Cherniltsev, A.
Gorbunova, E.
Issue Date: 2017
Publisher: International Multidisciplinary Scientific Geoconference
Citation: Cherniltsev A. Using the multilayer neural network for tasks of updating the user interface / A. Cherniltsev, E. Gorbunova // International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM. — 2017. — Vol. 17. — Iss. 21. — P. 743-750.
Abstract: This article presents issues related to model building for tasks of forming and modifying a custom user interface. We describe the possibility of using neural network methods to process the input data and classify the categories of user interfaces. The investigated task is solved by modeling the structure of an artificial neural network based on a multilayer perceptron. The preparation of a training data set and the use of this set for the training of neural network are provided. Input layer is considered a distributor of the signals from the external actions of network users with their interfaces. The output layer is considered a generator of some structural parameters of the user interface. Using the obtained parameters of the neural network the mathematical model constructed and analyzed for solving the above problem. The resulting data tested for various input data sets that were not used for training the network. In this paper, we investigate the possibility of applying the designed model for processing information needs of users, analysis and accumulation of the various parameters of user interface, and therefore applicability of this model for forming the most suitable solutions for users. © SGEM2017. All Rights Reserved.
Keywords: CLASSIFICATION
INTERFACE
MODEL
NEURAL NETWORK
UPDATING
CLASSIFICATION (OF INFORMATION)
INPUT OUTPUT PROGRAMS
INTERFACES (MATERIALS)
MODELS
MULTILAYER NEURAL NETWORKS
MULTILAYERS
NEURAL NETWORKS
DESIGNED MODELS
EXTERNAL ACTION
NETWORK USERS
NEURAL NETWORK METHOD
STRUCTURAL PARAMETER
SUITABLE SOLUTIONS
TRAINING DATA SETS
UPDATING
USER INTERFACES
URI: http://hdl.handle.net/10995/75312
metadata.dc.rights: info:eu-repo/semantics/openAccess
Conference name: 17th International Multidisciplinary Scientific GeoConference, SGEM 2017
Conference date: 29 June 2017 through 5 July 2017
SCOPUS ID: 85032505837
PURE ID: 6014719
ISSN: 1314-2704
DOI: 10.5593/sgem2017/21/S07.095
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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