作者：
Zhengbing Hu;Yevgeniy V. Bodyanskiy;Oleksii K. Tyshchenko
期刊：
Advances in Intelligent Systems and Computing,2018年 689: 186-203 ISSN：2194-5357
通讯作者：
Tyshchenko, O.K.
作者机构：
[Hu Z.] School of Educational Information Technology, Central China Normal University, 152 Louyu Road, Wuhan, 430079, China;[Bodyanskiy Y.V.; Tyshchenko O.K.] Control Systems Research Laboratory, Kharkiv National University of Radio Electronics, 14 Nauky Ave., Kharkiv, 61166, Ukraine
通讯机构：
[Tyshchenko, O.K.] C;Control Systems Research Laboratory, 14 Nauky Ave., Ukraine
会议名称：
12th International Scientific and Technical Conference Computer Science and Information Technologies, CSIT 2017
会议时间：
5 September 2017 through 8 September 2017
会议论文集名称：
Advances in Intelligent Systems and Computing II
摘要：
Ternary reversible latches on the basis of one- and two-qutrit permutative Muthukrishnan-Stroud (MS) gates were synthesized for the first time. Such gates can be physically implemented on the basis of liquid ion-trap quantum technology. The use of adaptive genetic algorithm allowed designing the circuits of latches that are optimal with respect to quantum cost, number of gates, and delay time. Comparisons of synthesized circuits with known results of other authors were carried out.
摘要：
An architecture and learning methods for deep neural networks that increase a number of layers and adjust their synaptic weights in an online mode are proposed in the article. The system's architecture is based on nodes of a special type (extended neo-fuzzy neurons) which possess enhanced approximating properties. A main feature of the proposed network is a learning process for each node that is performed sequentially in an online mode.
作者：
Hu, Zhengbing*;Bodyanskiy, Yevgeniy V.;Tyshchenko, Oleksii K.
期刊：
PROCEEDINGS OF THE 2017 12TH INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE ON COMPUTER SCIENCES AND INFORMATION TECHNOLOGIES (CSIT 2017), VOL. 1,2017年:514-519
通讯作者：
Hu, Zhengbing
作者机构：
[Hu, Zhengbing] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.;[Bodyanskiy, Yevgeniy V.; Tyshchenko, Oleksii K.] Kharkiv Natl Univ Radio Elect, Control Syst Res Lab, Kharkov, Ukraine.
通讯机构：
[Hu, Zhengbing] C;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.
会议名称：
12th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT)
会议时间：
SEP 05-08, 2017
会议地点：
Lviv, UKRAINE
会议主办单位：
[Hu, Zhengbing] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.^[Bodyanskiy, Yevgeniy V.;Tyshchenko, Oleksii K.] Kharkiv Natl Univ Radio Elect, Control Syst Res Lab, Kharkov, Ukraine.
关键词：
Group Method of Data Handling;Evolving System;Computational Intelligence;Growing Neuro-Fuzzy System;Machine Learning;Extended Neo-Fuzzy Neuron;Data Stream Processing;Deep Neural Network
摘要：
An architecture and learning methods for a growing neuro-fuzzy system that enlarges an amount of layers and tunes their synaptic weights in an online way are introduced in the paper. A structure of the hybrid system is built with the help of extended neo-fuzzy neurons which are characterized by improved approximating capabilities. The main peculiar feature of the introduced system is a learning method for each structural element that is carried out sequentially in an online manner.
作者机构：
[Hu, Zhengbing] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.;[Kotelianets, Vitalii; Gizun, Andrii; Gnatyuk, Viktor] Natl Aviat Univ, IT Secur Acad Dept, Kiev, Ukraine.;[Zhvrova, Tetiana] Kyiv Coll Commun, Cycle Comiss Math Modeling & Programming, Kiev, Ukraine.
会议名称：
4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T)
会议时间：
OCT 10-13, 2017
会议地点：
Kharkiv, UKRAINE
会议主办单位：
[Hu, Zhengbing] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.^[Gizun, Andrii;Gnatyuk, Viktor;Kotelianets, Vitalii] Natl Aviat Univ, IT Secur Acad Dept, Kiev, Ukraine.^[Zhvrova, Tetiana] Kyiv Coll Commun, Cycle Comiss Math Modeling & Programming, Kiev, Ukraine.
关键词：
cybersecurity;civil aviation;critical aviation information system;identification model;regulatory support;security model;security feature
摘要：
Cyber incidents can disrupt regular mode of information and telecommunication systems functioning and to cause the substantial material and image losses for the company. One of the approaches in incident management is the use of the theory of network-centric management for cyber incidents monitoring, but is not formalized stage of forming basic rules set. In this regard, in this work developed the method for rules set forming of cyber incidents extrapolation in network-centric monitoring, which allows to automate and increase accuracy operation of network-centric systems for information and telecommunication systems monitoring by determining possible types of cyber attacks and cyber incidents categories, forming vector-matrix of cyber incidents probability, cyber incidents ranging by their importance and determining limit values of probability, forming cyber incidents possibility indicators, and also development and establishment of cyber incidents extrapolation rules.
关键词：
The Error of Method;Labview;Thevenin Equivalent Circuit;NI USB 6009
摘要：
The error of method appears when measuring voltage by data acquisition (DAQ) devices because of neglecting their input parameters. The experimental determination of input parameters, such as the equivalent Thevenin input voltage and resistance, for 9 DAQ devices NI USB 6009 was carried out. Uncertainties for these parameters are given as well. The experimentally determined parameters compared with that given in the device documentation.
作者机构：
School of Educational Information Technology, Central China Normal University, Wuhan, China, China;Kharkiv National University of Radio Electronics, Kharkiv, Ukraine, Ukraine
摘要：
Context. A task of data classification under conditions of clusters’ overlapping is considered in this article. Besides that, it’s assumedthat information to be processed is given in the rank scale.Objective. It’s proposed to use a double neo-fuzzy neuron for classification which is a modification of a traditional neo-fuzzy neuronwith specially designed asymmetrical membership functions and improved approximating properties.Method. The double neo-fuzzy neuron (just like the traditional one) is designated for processing data given the scale of natural numbers.However, the situation may become complicated greatly if source data is not given in the numerical scale but in the ordinal one which is aquite common case for a wide variety of practical tasks.Results. A gradient minimization procedure with a variable learning step parameter was used for learning the double neo-fuzzy neuron.The proposed approach to fuzzy classification for data given in the ordinal scale based on the double neo-fuzzy neuron which is learnt withthe help of a high-speed algorithm possesses additional smoothing properties. The clustering accuracy for a training sample and the test one as well as the system’s learning speed were measured during experiments. The proposed architecture of the double neo-fuzzy neuron is a sort of compromise between a traditional neo-fuzzy neuron and its extended modification. This architecture demonstrates good performance in those cases when the results’ accuracy has more influence compared to the elapsed time used for data processing.Conclusions. Experimental implementation (for both artificial and real-world data) proved efficiency of the proposed techniques.During the experiments, properties of the proposed system were studied which confirmed usability of the proposed system for a wide range of Data Mining tasks.
作者：
Zhengbing Hu;Yevgeniy V. Bodyanskiy;Oleksii K. Tyshchenko;Viktoriia O. Samitova
期刊：
International Journal of Intelligent Systems and Applications,2017年9(1):67-74
通讯作者：
Hu, Z.
作者机构：
School of Educational Information Technology, Central China Normal University, Wuhan, China;Kharkiv National University of Radio Electronics, Kharkiv, Ukraine
通讯机构：
School of Educational Information Technology, Central China Normal University, Wuhan, China
作者：
Zhengbing Hu;Igor A. Tereykovski;Lyudmila O. Tereykovska;Volodymyr V. Pogorelov
期刊：
International Journal of Intelligent Systems and Applications,2017年9(10):57-62 ISSN：2074-9058
作者机构：
School of Educational Information Technology, Central China Normal University, Wuhan, China;Faculty of Applied Mathematics, National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute', Kyiv, Ukraine;Kyiv National University of Construction and Architecture, Kyiv, Ukraine
关键词：
Hidden neuron;Hidden neuron layer;Neuro-network model generalization;Structure adaptation;Structure of multilayer perceptron
作者：
Zhengbing Hu;Yevgeniy V. Bodyanskiy;Oleksii K. Tyshchenko;Viktoriia O. Samitova
期刊：
International Journal of Intelligent Systems and Applications,2017年9(2):1-9
作者机构：
School of Educational Information Technology, Central China Normal University, Wuhan, China;Kharkiv National University of Radio Electronics, Kharkiv, Ukraine
关键词：
Computational intelligence;FCM;Likelihood function;Machine learning;Membership function;Ordinal data
期刊：
International Journal of Intelligent Systems and Applications,2016年8(11):9-18 ISSN：2074-9058
作者机构：
School of Educational Information Technology, Central China Normal University, China;Faculty of Applied Mathematics, National Technical University of Ukraine Kyiv Polytechnic Institute, Ukraine
作者：
Hu, Zhengbing*;Bodyanskiy, Yevgeniy V.;Tyshchenko, Oleksii K.
期刊：
2016 XITH INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE COMPUTER SCIENCES AND INFORMATION TECHNOLOGIES (CSIT),2016年:119-122
通讯作者：
Hu, Zhengbing
作者机构：
[Hu, Zhengbing] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Bodyanskiy, Yevgeniy V.; Tyshchenko, Oleksii K.] Kharkiv Natl Univ Radio Elect, Control Syst Res Lab, Kharkov, Ukraine.
通讯机构：
[Hu, Zhengbing] C;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.
关键词：
Computational Intelligence;Data Stream Processing;Neuro-Fuzzy System;Fuzzy Clustering;Machine Learning;Evolving System
摘要：
A cascade deep learning system (based on neuro-fuzzy nodes) and its online learning procedure are proposed in this paper. The system is based on nodes of a special type. A goal function of a special type is used for possibilistic high-dimensional fuzzy clustering. To estimate a clustering quality of data processing, an optimal value of a cluster validity index is used.
关键词：
component;neural network;thermocouple;drift of conversion characteristic of thermocouples;thermoelectric inhomogeneity of thermocouples
摘要：
This paper considers the usage of artificial intelligence, in particular, neural networks, to correct and compensate thermocouple errors. There are the correction of the thermocouple tolerance, the error due to conversion characteristic drift under the influence of high operating temperatures as well as the compensation of the error due to acquired thermoelectric inhomogeneity of thermocouple legs proposed in this paper. The correction is carried out using individual mathematical models based on neural networks. It is proposed the neural network method for controlling a temperature field to compensate the error due to acquired thermoelectric inhomogeneity.
期刊：
International Journal of Intelligent Systems and Applications,2016年8(12):67-64 ISSN：2074-9058
作者机构：
School of Educational Information Technology, Central China Normal University, No. 152 Louyu Road, Wuhan, 430079, China;National Technical University of Ukraine "Kiev Polytechnic Institute", Kiev, 03057, Ukraine;Taras Shevchenko National University of Kiev, Volodymyrska Street, 64/13, Kiev, 01601, Ukraine
作者：
Zhengbing Hu;Yevgeniy V. Bodyanskiy;Oleksii K. Tyshchenko;Olena O. Boiko
期刊：
International Journal of Intelligent Systems and Applications,2016年8(9):1-7
作者机构：
School of Educational Information Technology, Central China Normal University, Wuhan, China;Kharkiv National University of Radio Electronics, Kharkiv, Ukraine
摘要：
Multiple-valued logic is a promising choice for future computer technologies, which provides a set of advantages comparing to binary circuits. We have developed an adaptive genetic algorithm for ternary reversible circuits using Muthukrishnan-Stroud gates. The method for chromosomes coding, as well as a reasonable choice of algorithm parameters, allowed obtaining circuits for ternary arithmetic devices, which are better than other known methods in terms of quantum cost, delay time and amount of input ancillary and output garbage qutrits. Based on our realization of ternary parallel full-adder we synthesized reversible ternary parallel adder/subtractor, which has better parameters over the previously reported devices.
