stochastic mode
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Author(s):  
Lenin Kanagasabai

<span lang="IN">This </span><span>work presents Arctic Char </span><span lang="EN-GB">Algorithm (ACA) for solving optimal reactive power problem.</span><span> In North America movement of Arctic char phenomenon is one among the twelve-monthly innate actions. Deeds of Arctic char have been imitated to design the algorithm. In stochastic mode solutions are initialized with one segment on every side of to the route ascendancy; particularly in between lower bound and upper bounds. Previous to the movement, Arctic char come to a decision about the passageway based on their perception. This implies stochastic mix up of control parameters to push the Arctic char groups (preliminary solution) in mutual pathway (evolutionary operators). Projected Arctic Char </span><span lang="EN-GB">Algorithm (ACA) </span><span>has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss extensively.</span>



2019 ◽  
Vol 4 (3) ◽  
pp. 8-14
Author(s):  
Andrei N. Volobuev ◽  
Vasiliy F. Pyatin ◽  
Natalya P. Romanchuk ◽  
Petr I. Romanchuk ◽  
Svetlana V. Bulgakova

Objectives -research of stochastic brain function in respect to creation of artificial intelligence. Material and methods. Mathematical modeling principles were used for simulation of brain functioning in a stochastic mode. Results. Two types of brain activity were considered: determinated type, usually modeled using the perceptron, and stochastic type. It is shown, that stochastic brain function modeling is the necessary condition for AI to become capable of creativity, generation of new knowledge. Mathematical modeling of a neural network of the cerebral cortex, consisting of the set of the cyclic neuronal circuits (memory units), was performed for the stochastic mode of brain functioning. Models of "two-dimensional" and "one-dimensional" brain were analyzed. The pattern of excitation in memory units was calculated in the "one-dimensional" brain model. Conclusion. Relying on the knowledge of the stochastic mode of brain function, a way of creation of AI can be offered. а-rhythm of a patient is a recommended focus of the therapist's attention in diagnostics and treatment of brain disorders. It was noted, that the alpha wave amplitude and frequency could indicate the cognitive, creative and intuitive abilities of a person.



2018 ◽  
Vol 144 (715) ◽  
pp. 1975-1990 ◽  
Author(s):  
Matthias Zacharuk ◽  
Stamen I. Dolaptchiev ◽  
Ulrich Achatz ◽  
Ilya Timofeyev


2017 ◽  
Vol 189 (2) ◽  
pp. 131-138
Author(s):  
Igor I. Usoltsev ◽  
Talgat R. Kilmatov ◽  
Aleksander N. Vrazhkin

Data of observations on drifting buoys in the western Okhotsk Sea are presented. Quasi-stochastic mode of the buoys drift under forcing of atmospheric cyclone is noted. The drift is analyzed jointly with analysis of the wind field and the sea surface satellite altimetry. The buoy drift trajectories are modeled under separate influence of the wind-driven and geostrophic flows. There is concluded that both wind-driven and geostrophic currents at the sea surface should be accounted for forecasting of drift for buoys or any floating objects.



2015 ◽  
Vol 13 (2) ◽  
pp. 297-314 ◽  
Author(s):  
Ankita Jain ◽  
Ilya Timofeyev ◽  
Eric Vanden-Eijnden
Keyword(s):  


2014 ◽  
Vol 106 (4) ◽  
pp. 44003 ◽  
Author(s):  
Marek Stastna ◽  
Francis J. Poulin


2013 ◽  
Vol 110 (24) ◽  
Author(s):  
M. Schmuck ◽  
M. Pradas ◽  
S. Kalliadasis ◽  
G. A. Pavliotis


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