Automatic Search of Reliability Function by Symbolic Regression
A reliability index of various electronics is determined by the experimental data of tests for different values of parameters of the equipment. The received data are collected in bulky tables and references. This paper presents modern numerical approach, allowing to compile the experimental data on changes of reliability index not in the form of tables but as a function of the operating parameters of the devices. The methodology is based on the method of network operator for the design of the optimal structure of function and selection of its parameters. The network operator method belongs to a class of methods of symbolic regression and provides an evolutionary search for the best compositions of mathematical expressions on the space of elementary structures. The method allows you to automatically receive the required description of the functional dependencies. The effectiveness of the method is demonstrated by the example of searching the law, which describes the change in the failure rate depending on three parameters that characterize its constructive and technological performance and operating conditions.
In this work, in order of development of the previously proposed decision support system to counteract the development of infectious diseases (DSS «CDID») it is proposed evolutionary model (EM), that extends the capabilities of forecast – analytical studies on the spread of infectious disease processes for individual cities and areas of the country as a whole, as well as early assessment of ways solutions to the problems of prophylaxis and therapy in the study territories.
An actuating device complex motion mathematical model of automated vacuum processing equipment is developed. The model allows for controlling evenness of the thin filming aimed at improving its evenness. Manufacturing advantages of the coordinate actuating devices compared to planetary design are given, as well as main ways of controlling and improving vacuum thin film deposition evenness.
In an uncertain world, decisions by market participants are based on expectations. Thus, sentiment indicators reflecting expectations are proven at predicting economic variables. However, survey respondents largely perceive the world through media reports. Typically, crude media information, like word-count indices, is used in the prediction of macroeconomic and financial variables. Here, we employ a rich data set provided by Media Tenor International, based on sentiment analysis of opinion-leading media in Germany from 2001 to 2014, transformed into several monthly indices. German industrial production is predicted in a real-time out-of-sample forecasting experiment using more than 17,000 models formed of all possible combinations with a maximum of 3 out of 48 macroeconomic, survey, and media indicators. Media data are indispensable for the prediction of German industrial production both for individual models and as a part of combined forecasts, particularly during the global financial crisis.
The companies that are IT-industry leaders perform from several tens to several hundreds of projects simultaneously. The main problem is to decide whether the project is acceptable to the current strategic goals and resource limits of a company or not. This leads firms to an issue of a project portfolio formation; therefore, the challenge is to choose the subset of all projects which satisfy the strategic objectives of a company in the best way. In this present article we propose the multi-objective mathematical model of the project portfolio formation problem, defined on the fuzzy trapezoidal numbers. We provide an overview of methods for solving this problem, which are a branch and bound approach, an adaptive parameter variation scheme based on the epsilon-constraint method, ant colony optimization method and genetic algorithm. After analysis, we choose ant colony optimization method and SPEA II method, which is a modification of a genetic algorithm. We describe the implementation of these methods applied to the project portfolio formation problem. The ant colony optimization is based on the max min ant system with one pheromone structure and one ant colony. Three modification of our SPEA II implementation were considered. The first adaptation uses the binary tournament selection, while the second requires the rank selection method. The last one is based on another variant of generating initial population. The part of the population is generated by a non-random manner on the basis of solving a one-criterion optimization problem. This fact makes the population more strongly than an initial population, which is generated completely by random. Comparing of ant colony optimization algorithm and three modifications of a genetic algorithm was performed. We use the following parameters: speed of execution and the C-metric between each pair of algorithms. Genetic algorithm with non-random initial population show better results than other methods. Thus, we propose using this algorithm for solving project portfolio formation problem.
The paper is devoted to the description of a new multi-purpose intellectual decision support system. We present the algorithms used and the results achieved in applying the system to analyzing and forecasting the sea ice area in the Northern Hemisphere. The impact of solar radiation on the changes in the sea ice area was confirmed. Application of interval neural nets to medium-term forecasting of sea ice area changes was justified.
In most educational institutions studies of such courses as "Electronic Engineering" , "Electronics", "Fundamentals of electronic circuits", "Fundamentals of Radio Electronics and Communications", "General Communication Theory", etc. , provision laboratory workshops to allow students to gain a deeper understanding of the discipline. However, even a well- equipped laboratory cannot cover the entire range of discipline that leads to gaps in practical training. In such cases it recommended to include various computer modeling system to the educational process which will help to visualize physical processes in the electronic circuits.