Neuro-fuzzy system for prediction of telecommunication channel load

Polshchykova

et al. 2019

Lobachevskii J Math

In this paper decision support algorithm for choosing the processing means of natural language big data arrays is proposed. In the process the algorithm uses the program for evaluating the effectiveness of text analyzers. This program is based on the operation of a fuzzy choice system, which serves to calculate the integral indicator of the text analyzer effectiveness. The quality and efficiency of getting answers to test questions are taken into account when evaluating the effectiveness of text analyzers.

“…It is possible to find the resulting evaluation of a software text analyzer effectiveness by calculating a certain integral index with the help of a fuzzy inference [6][7][8][9][10][11].…”

Section: Indicators Of a Text Analyzer Effectivenessmentioning

confidence: 99%

The Algorithm for Decision-Making Supporting on the Selection of Processing Means for Big Arrays of Natural Language Data

Polshchykova

et al. 2019

Lobachevskii J Math

“…Merits of MANET usage are rapid deployment, high subsistence, ability to provide communication in case of dynamically changing network topology. The data traffic in MANET is formed by the messages containing control signals, text, graphic and table information [2][3][4][5][6][7]. Upon delivery of these messages virtual connections mode is used in order to support the reliability, integrity of transmitted data and avoiding network overloads by the transport layer means.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Model of Message Delivery in a Mobile Ad Hoc Network

Konstantinov

2017 IEEE 11th International Conference on Application of Information and Communication Technologies (AICT)

et al. 2017

Self Cite

“…fuzzy logic and neural networks[13][14][15][16][17][18]. The following values are provided to this system input[19][20][21][22]:…”

mentioning

confidence: 99%

Neuro-fuzzy control of data sending in a mobile ad hoc network

J. Fundam and Appl Sci.

Zdorovtsov

2018

The article is aimed at data transmission efficiency increase in a mobile ad hoc network, functioning to ensure the exchange of information in emergency situations. The algorithm for neuro-fuzzy control of data sending intensity in this network is proposed. The algorithm provides the measurement of latency period confirmation and the calculation of a moving average of this value, as well as a periodic recalculation of an inter-packet gap by performing neuro-fuzzy inference procedure. By using the algorithm an adaptive change of data sending intensity is provided in the framework of the established logical connection. Simulation experiments showed that the use of the proposed algorithm reduces the number of retransmissions and the average transmission time of data streams in a test network. Keywords: mobile ad hoc network, emergencies, the intensity of data sending, algorithm. dynamically changing topology (random processes of movement, destruction, addition, the turning on and turning off of nodes). Mobile ad hoc networks (MANET) have the specified abilities [1-3].