Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Name

Shumkov Yevgeniy Aleksandrovich

Scholastic degree


Academic rank

—

Honorary rank

—

Organization, job position

Kuban State Technological University
   

Web site url

—

Email

sneveld@yandex.ru


Articles count: 17

161 kb

SIMULATION OF THE HOTEL

abstract 0911307079 issue 91 pp. 1124 – 1133 30.09.2013 ru 1318
In the article, we have discussed the question of simulating the operation of a hotel complex with the help of fuzzy inference rules
130 kb

GENETIC SEARCH TOPOLOGY OF NEURAL NETWORK MODELS

abstract 0931309086 issue 93 pp. 1251 – 1260 30.11.2013 ru 1362
In the article we consider the topology of genetic search of neural network models
147 kb

USING GENETIC ALGORITHMS FOR TRAINING NEURAL NETWORKS

abstract 0911307078 issue 91 pp. 1114 – 1123 30.09.2013 ru 1552
In this article we have shown how to find sub-optimal neural networks using genetic algorithms
121 kb

RESEARCH OF TECHNICAL INDICATOR MACD

abstract 0641010025 issue 64 pp. 327 – 336 22.12.2010 ru 1838
In the article popular technical MACD indicator is considered. Various parameters of the indicator about revealing of statistical advantage are investigated. The variant of use of genetic algorithms for a problem of search of parameters of the indicator is shown
141 kb

STATISTICAL ANALYSIS OF TECHNICAL INDICATORS

abstract 0641010026 issue 64 pp. 337 – 345 22.12.2010 ru 1839
In the article, popular technical «Stochastic Oscillator» indicator is considered. Various trading strategies based on the indicator are researched; the parameters with statistical advantage are revealed
149 kb

RECOGNITION OF FIGURES OF THE TECHNICAL ANALYSIS BY MEANS OF NEURAL NETWORKS

abstract 0651101025 issue 65 pp. 303 – 312 31.01.2011 ru 1995
In this article, the approach to the decision of a problem of recognition of figures of the technical analysis with use of artificial neural networks is offered. Also, the problem of forecasting of the further movement of time series is considered
116 kb

HIGH-SPEED METHOD OF MULTILAYERED PERCEPTRON TRAINING

abstract 0651101024 issue 65 pp. 294 – 302 31.01.2011 ru 2152
In this article the high-speed method of multilayered perceptron learning which differs in the high speed of training is offered. Results of comparison of a high-speed method of learning with standard methods are resulted
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