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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.
Abstract: With the growing demand for telecommunications services, the number of calls to telecommunications companies related to issues of using services, setting up and maintaining equipment, as well as resolving possible problems arising in the process of using services is also growing. From the point of view of system analysis, the problem is the mismatch between the existing and the required (target) state of the system for a given state of the environment at the moment in time. Based on this definition, we consider the problem of the subscriber of the cellular network a mismatch between the existing and the required state of the cellular network in this state of the environment at the moment in time. The state of the cellular network is characterized by the functioning of all devices, the proposed range of services. A short time for analyzing problem situations and making decisions, a large amount of information characterizing the current situation, the difficulty of solving poorly formalized and poorly structured tasks in the absence of complete and reliable information about the state of the cellular communication network and the functioning of its elements lead to a mismatch of human capabilities to effectively solve these problems. In this regard, the development and implementation of a precedent based neural network expert system for solving the problems of subscribers of a cellular communication network is an urgent scientific and technical task.
Ahmad AbdulQadir AlRababah, “Problems Solving of Cell Subscribers based on Expert Systems Neural Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101232
@article{AlRababah2019,
title = {Problems Solving of Cell Subscribers based on Expert Systems Neural Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101232},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101232},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Ahmad AbdulQadir AlRababah}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.