Katanov State University of Khakassia

Imeni Vladimira Il’icha Lenina, Russia

Katanov State University of Khakassia

Imeni Vladimira Il’icha Lenina, Russia
SEARCH FILTERS
Time filter
Source Type

Engel E.A.,Katanov State University of Khakassia | Kovalev I.V.,Siberian State Aerospace University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2017

This paper presents a multi-agent adaptive fuzzy neuronet for hourly solar irradiance forecasting under random perturbations. The training algorithm of the multi-agent adaptive fuzzy neuronet must find the optimal network configuration within an architecture space. In a multidimensional search space where the optimum dimension is unknown, the training algorithm must seek both positional and dimensional optima. The simulation results show that multi-dimensional Particle Swarm Optimization outperforms Genetic algorithm in training the effective multi-agent adaptive fuzzy neuronet for hourly solar irradiance forecasting. © Springer International Publishing AG 2017.


Engel E.A.,Katanov State University of Khakassia
Proceedings - 2016 International Conference on Engineering and Telecommunication, EnT 2016 | Year: 2016

This paper presents a method for modeling, sizing and cost analysis of a photovoltaic system with battery on the basis of the multi-agent adaptive fuzzy neuronet. The goal of this research is to find the best configuration of the system and the optimal sizing coefficient of a photovoltaic system on the basis of the multi-agent adaptive fuzzy neuronet. The simulation results show that the effectiveness of the proposed method is better than the genetic algorithm in sizing of a photovoltaic system with battery. © 2016 IEEE.


Engel E.A.,Katanov State University of Khakassia | Kovalev I.V.,Siberian State Aerospace University | Engel N.E.,Katanov State University of Khakassia
IOP Conference Series: Materials Science and Engineering | Year: 2016

This paper presents model of interaction in Smart Grid on the basis of multi-agent system. The use of travelling waves in the multi-agent system describes the behavior of the Smart Grid from the local point, which is being the complement of the conventional approach. The simulation results show that the absorption of the wave in the distributed multi-agent systems is effectively simulated the interaction in Smart Grid. © Published under licence by IOP Publishing Ltd.


Engel E.A.,Katanov State University of Khakassia | Kovalev I.V.,Siberian State Aerospace University | Engel N.E.,Katanov State University of Khakassia
IOP Conference Series: Materials Science and Engineering | Year: 2016

This paper presents algorithm for generating neuroevolutionary multi-agent system that allows agents to learn from high-quality activities. Dissimilar traditional learning algorithms proposed algorithm combines student-teacher of-line learning and teaching agents based on sufficient activities producing by any agent in its subculture. The simulation studies demonstrated that the proposed algorithm is effective at rapidly generating near-optimal control agents. © Published under licence by IOP Publishing Ltd.


Baidyshev V.S.,Katanov State University of Khakassia | Gafner Y.Y.,Katanov State University of Khakassia | Samsonov V.M.,Tver State University | Bembel A.G.,Tver State University
Crystallography Reports | Year: 2015

The boundaries of thermal stability of the initial fcc phase in aluminum and lead clusters up to 3 nm in diameter have been investigated by the method of molecular dynamics using a modified tight-binding potential TB-SMA. It is shown that in small Al and Pb clusters the initial fcc phase passes into different structural modifications due the temperature factor. The polytype transition temperature has been found to approach the cluster melting temperature with an increase in the nanoparticle size. It is established that geometric “magic” numbers play an important role in the formation of structure of Al clusters (in contrast to Pb clusters). © 2015, Pleiades Publishing, Inc.


Chepkasov I.V.,Katanov State University of Khakassia | Popov Z.I.,RAS Kirensky Institute of Physics
IOP Conference Series: Materials Science and Engineering | Year: 2015

Molecular dynamics method using the tight-binding potential to carry out simulation of ultrafast heating of the synthesized particles from the gas phase to a temperature T= 600K and T= 900K, at which the particles were kept about 10 ns. As a result of the simulation revealed that the method of ultrafast heating the particles to high temperatures virtually eliminates the possibility of a clusters of defective education, but as a result of the heat treatment, the some of investigated particles can disconnect (burst) into smaller clusters. © Published under licence by IOP Publishing Ltd.


Chepkasov I.V.,Katanov State University of Khakassia | Redel L.V.,Katanov State University of Khakassia
IOP Conference Series: Materials Science and Engineering | Year: 2015

On the basis of our former simulations, we conclude that the heat capacity in the case of isolated free clusters can exceed that of a bulk material. It was found that at T=200K the increase in the Cu nanocluster heat capacity (D = 6nm) was only 10%, decreasing with growing nanoparticle proportionally to the reduction in the fraction of surface atoms. Thus, the considerably larger heat capacities of copper nanostructures observed in the experimental works cannot be related to the characteristics of free clusters. In our view, these properties of a nanomaterial can be associated with the degree of agglomeration of its constituent particles, i.e., the interphase boundaries and the increase in the root-mean-square displacements of atoms on the combined surface of the interconnected nanoclusters can have a strong effect. To test the above hypothesis, we took copper clusters of various sizes (4071-15149 atoms) that we produced when simulating the synthesis of Cu nanoparticles. Thus, in our molecular-dynamics experiments using a tight-binding potential at high temperatures, we failed to properly assess the role of the interphase boundaries in calculating the heat capacity of nanoparticles. The reason was the mass diffusion of Cu atoms to impart an energetically more favorable shape and structure to the cluster. At low temperatures, the heat capacity of the clusters exceeded that of the bulk same by a value from 10% to 17%. Consequently, the Cu clusters produced in direct experiments cannot be immediately applied in devices using the thermal energy of such clusters, because their external shape and internal structure are nonideal. © Published under licence by IOP Publishing Ltd.


Gafner Yu.Ya.,Katanov State University of Khakassia | Gafner S.L.,Katanov State University of Khakassia
IOP Conference Series: Materials Science and Engineering | Year: 2015

The opportunity of transition metals nanoclusters' usage as a data bits in memory devices for the recording transition "order-disorder" has been analyzed. Therefore, with the help of the molecular dynamics method on the basis of TB-SMA potential the simulation of metal nanoparticles (D = 1.6 - 5.0 nm) crystallization processes have been studied. Influence of various conditions of crystallization on formation of internal structure in metal nanoclusters is investigated. The stability boundaries of various crystalline isomers are analyzed. The obtained dependences are compared with the corresponding data obtained for copper and nickel nanoparticles having similar sizes. The limiting size of nanoparticles is determined, for which a structural "order-disorder" transition necessary for the data recording is still possible. © Published under licence by IOP Publishing Ltd.


Gafner Y.Y.,Katanov State University of Khakassia | Baidyshev V.S.,Katanov State University of Khakassia
IOP Conference Series: Materials Science and Engineering | Year: 2015

The boundaries of thermal stability of the initial face-centered cubic (fcc) phase in perfect aluminum clusters with a diameter up to 3 nm have been investigated by the molecular dynamics method using a modified tight binding (TB-SMA) potential. Based on the performed computer analysis, it has been concluded that, in most cases, for aluminum clusters with sizes up to D = 2.5 nm, the most stable configuration is the structure with pentagonal symmetry. With a further increase in the number of atoms, the fcc structure becomes more stable. The influence of the degree of disorder of nanocompacted aluminum particles up to 4 nm in diameter on the formation of a crystal structure during heat treatment has been analyzed. It has been shown that, under the effect of the temperature factor, the clusters undergo a transition from the initial fcc phase to other structural modifications, including those with pentagonal symmetry, even in the case of clusters with fairly large sizes. © Published under licence by IOP Publishing Ltd.


Udodov V.N.,Katanov State University of Khakassia
Physics of the Solid State | Year: 2015

The general interpolation formulas, which generalize the classical consequences of the static scaling hypothesis for phase transitions with variation in the temperature and field, have been proposed. The classical results have been derived from these formulas as a limiting partial case for the asymptotic proximity to a positive critical temperature. It has also been shown that some consequences of the scaling hypothesis also remain correct at a zero critical temperature; however, for example, the Essam–Fisher equality changes its form in the latter case, namely, the numeral two on the right-hand side is replaced by unity. © 2015, Pleiades Publishing, Ltd.

Loading Katanov State University of Khakassia collaborators
Loading Katanov State University of Khakassia collaborators