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Cybernetics and programming
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MAIN PAGE > Journal "Cybernetics and programming" > Contents of Issue № 06/2017
This issue is currently being formed. All articles presented on this page have already been included in this issue, are considered published, and will remain unchanged in the final version of the issue along with other metadata of the articles.
Учредитель: Даниленко Василий Иванович, w.danilenko@nbpublish.com
Главный редактор: Сидоркина Ирина Геннадьевна, доктор технических наук, igs592000@mail.ru
Contents of Issue № 06/2017
Question at hand
Agibalov O.I., Ventsov N.N. - Assessing Time Dependencies of the Genetic Algorithm Carried Out on CPU and GPU pp. 1-8

DOI:
10.25136/2306-4196.2017.6.24509

Abstract: The subject of the research is the problem of choosing the most efficient hardware architecture to execute a stochastic population-based algorithm. The object of the research is the genetic algorithm carried out using the central processing unit (CPU) or graphics processing unit (GPU). In their research the authors give results of a computational experiment aimed at comparing time dependencies of the genetic algorithm executed on the central processing unit or graphics processing unit based on the number of chromosomes used. The authors also compare the overall time of task solutions and time necessary to initialize CPU and GPU. Due to the fact that it was impossible to obtain the precise time assessment of the genetic algorithm, the authors have developed a loose time assessment of GPU-algorithm for 3000 chromosomes. The research method is based on the experimental assessment of time dependencies of the genetic algorithm executed using CPU or GPU based on the number of species in the population. The computational complexity of the genetic algorithm for both types of processing units is approximately O(n)-O(n2). Based on the results the authors have stated that in cases when the population is 2000-2500 chromosomes, the genetic algorithm should be better executed using CPU and when the population exceeds 3000-4000 chromosomes it is better to execute it using GPU. Such unclarity of efficiency frontiers is caused by the stochastic nature of the genetic algorithm. It should be also noted that these frontiers for choosing the most efficient hardware architecture are right exclusively for solving the above mentioned task. The results will be different for simpler tasks and other hardware and software conditions. The present research focuses not only on the numerical assessment of efficiency frontiers but on whether such crossing point can be defined or not. 
Automated systems of engineering process administration
Ivanov M.A., Savelyev A.O., Saklakov V.M. - Software Design for Energy-Efficient Mechatronic Devices with Intelligent Control Systems pp. 9-18

DOI:
10.25136/2306-4196.2017.6.24574

Abstract: Today alternative energy technologies are a well-established practice in the development of energy resources. The present article is devoted to a narrow aspect thereof, implementation of solar panels. Every year the number of solar panels put into commission increases by 25 - 35 %. The authors of the article offer their own solution in this sphere that allows to manage solar panels in real-time mode and provide for their automatic checkout and productivity analysis. Previous articles of the authors describe the development of the prototype hardware and the present article describes software methods and algorithms. The research method used by the authors to develop software is The Analytic Hierarchy Process (AHP or Saaty Method). The scientific novelty of the research is caused by the fact that the authors develop the software for implementing methods and algorithms of mechatronic devices complex divided into two modules, service software and software support of the control module. Implementation of this software has allowed to complete the alignment of automated collection and accumulation of information based on set working parameters, visualisation of these parameters of solar battery accumulators and transformers working as part of the solar electroenergy module even when data is lost or damaged or when emergency occurs. 
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