Showing papers by "Zhengbing Hu published in 2016"
01 Sep 2016
TL;DR: A cascade deep learning system (based on neuro-fuzzy nodes) and its online learning procedure are proposed in this paper and an optimal value of a cluster validity index is used.
Abstract: 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.
21 citations
TL;DR: Neo-fuzzy elements are used as nodes for an evolving cascade system as mentioned in this paper, which can be used for solving a wide range of Data Mining tasks (namely time series forecasting).
Abstract: Neo-fuzzy elements are used as nodes for an evolving cascade system. The proposed system can tune both its parameters and architecture in an online mode. It can be used for solving a wide range of Data Mining tasks (namely time series forecasting). The evolving cascade system with neo-fuzzy nodes can process rather large data sets with high speed and effectiveness.
19 citations
TL;DR: The article deals with the issues of the security of distributed and scalable computer systems based on the risk-based approach and proposes comprehensive analytical risks assessments for the security risk level in the distributed computer system.
Abstract: The article deals with the issues of the security of distributed and scalable computer systems based on the risk-based approach. The main existing methods for predicting the consequences of the dangerous actions of the intrusion agents are described. There is shown a generalized structural scheme of job manager in the context of a risk-based approach. Suggested analytical assessments for the security risk level in the distributed computer systems allow performing the critical t ime values forecast for the situation analysis and decisionmaking for the current configuration o f a distributed computer system. These assessments are based on the number of used nodes and data links channels, the number of act ive security and monitoring mechanisms at the current period, as well as on the intensity of the security threats realization and on the activation intensity of the intrusion prevention mechanis ms. The proposed comprehensive analytical risks assessments allow analyzing the dynamics of intrusions processes, the dynamics of the security level recovery and the corresponding dynamics of the risks level in the distributed computer system.
19 citations
06 Oct 2016
TL;DR: A deep cascade system (based on neuro-fuzzy nodes) and its online learning procedure are proposed and a neuron's architecture of a special type is introduced to assess a clustering quality of data processing.
Abstract: A deep cascade system (based on neuro-fuzzy nodes) and its online learning procedure are proposed in this paper. A number of layers can grow unlimitedly during a self-learning procedure. The system is based on nodes of a special type. A goal function of a special type is used for probabilistic high-dimensional fuzzy clustering. To assess a clustering quality of data processing, a neuron's architecture of a special type is introduced.
15 citations
TL;DR: The integrated experimental research of basic classes of searching methods for multiplicative inverse in the ring of integers modulo m is conducted for the first time and the analytical formulas for these calculations of random access memory necessary space when operated at k-ary RS-algorithms and their modifications are shown.
Abstract: In this article an investigation into search operations for the multip licat ive inverse in the ring of integers modulo m for Error Control Coding tasks and for data security is shown. The classificat ion of the searching operation of the multip licat ive inverse in the ring of integers modulo m is provided. The best values of parameters for Joye-Paillier method and Lehmer algorithm were also found. The improved Bradley modification for the extended Euclidean algorithm is also offered, which g ives the operating speed improvement for 10-15%. The integrated experimental research of basic classes of searching methods for multiplicative inverse in the ring of integers modulo m is conducted for the first time and the analytical formulas for these calculations of random access memory necessary space when operated at k-ary RS-algorithms and their modifications are shown.
13 citations
TL;DR: In this paper, a new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed, which is formed with adaptive self-organizing Kohonen maps in a parallel processing mode.
Abstract: A new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed. The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode. Their learning procedure is carried out with different parameters that define a nature of cluster borders' blurriness. Clusters' quality is estimated in an online mode with the help of a modified partition coefficient which is calculated in a recurrent form. A final result is chosen by the best neuro-fuzzy self-organizing Kohonen map.
12 citations
TL;DR: An evolving weighted neuro-neo-fuzzy- ANARX model and its learn ing procedures are introduced in the article and may provide online processing data streams.
Abstract: An evolving weighted neuro-neo-fuzzy- ANARX model and its learn ing procedures are introduced in the article. This system is basically used for time series forecasting. It's based on neo-fuzzy elements. This system may be considered as a pool of elements that process data in a parallel manner. The proposed evolving system may provide online processing data streams.
7 citations
01 Aug 2016
TL;DR: An adaptive genetic algorithm for ternary reversible circuits using Muthukrishnan-Stroud gates is developed, which allows 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.
Abstract: 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.
2 citations
Posted Content•
TL;DR: The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode with different parameters that define a nature of cluster borders' blurriness.
Abstract: A new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed. The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode. A final result is chosen by the best neuro-fuzzy self-organizing Kohonen map.
1 citations
Posted Content•
TL;DR: The evolving cascade system with neo-fuzzy nodes can process rather large data sets with high speed and effectiveness and can tune both its parameters and architecture in an online mode.
Abstract: Neo-fuzzy elements are used as nodes for an evolving cascade system. The proposed system can tune both its parameters and architecture in an online mode. It can be used for solving a wide range of Data Mining tasks (namely time series forecasting). The evolving cascade system with neo-fuzzy nodes can process rather large data sets with high speed and effectiveness.
1 citations
Posted Content•
TL;DR: An evolving weighted neuro-neo-fuzzy-ANARX model and its learning procedures are introduced in this article, which is basically used for time series forecasting and is considered as a pool of elements that process data in a parallel manner.
Abstract: An evolving weighted neuro-neo-fuzzy-ANARX model and its learning procedures are introduced in the article. This system is basically used for time series forecasting. This system may be considered as a pool of elements that process data in a parallel manner. The proposed evolving system may provide online processing data streams.