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MINISTRY OF EDUCATION AND SCIENCE OF THE RUSSIAN
FEDERATION
National Research Nuclear University “MEPhI”
Faculty of Management and Economics of High Technologies
Khusniyzrov M.R.
“The development of tools for monitoring and forecasting of sciencetechnological area of “Energy efficiency and conservation”
Master’s degree thesis synopsis
Moscow 2013
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WORK GENERAL PATTERN
Above all relevance of the study is determined by the need of Russia to move in the path of
innovative development.
Modern technology markets are formed on the basis of the mass technology. Coming up related
to each other sets of products, tools, manufactures, consumers who have to coherent and codevelop. Technical-economic systems, representing some commonality of overcome challenges
and windows of opportunity to resolve them executed as scientific-technological areas (STA).
STA improvement involves control of improvement process of research results, research
technology, manufacturing technology, and consumer technology. It is important to ensure their
consistent, "synchronous" development. This requires to maintain a ratio of properties in the
system, ensuring the preservation of the coherence. This involves forecasting of trends as a
whole, the definition of such options to improve the facilities that support each other and don’t
destroy the coherence.
Therefore the development, research and evaluation of tools for forecasting, monitoring,
application of the results of monitoring for process innovation development is important.
The aim of the research is to determine the characteristics of forecasting in the transition to an
economy of innovation, the development of adequate means for the prediction and assessment of
their quality, the development of monitoring plans and methods of generating information
products.
In this context, formulated the following research objectives:
1) problems identification of modern scientific-technological trends forecasting and basement of
their nature
2) development of models for predicting
3) development of expert networks evaluation criteria
4) formation of experts network
5) monitoring the sectors of scientific-technological area "energy efficiency and conservation,"
analysis of the monitoring results
6) development of recommendations on the use of the results in the formation of state scientifictechnological forecasting system.
The object of research is forecasting tools of scientific-technological areas development.
The subject of the study is forecasting objects identification models, criteria for evaluating the
effectiveness of expert networks, methods and results of monitoring.
Scientific innovation, in principle, is to develop new approaches to forecasting problems
solving in the transition to an economy of innovation: the development of methods of forming
and evaluating of expert networks effectiveness to predict the innovation development processes,
identification of prediction objects, preserving consistency in innovative development,
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development of methods of monitoring and analysis of the results in the practical field of
"energy efficiency and conservation."
In terms of specification of applied scientific innovation at the session will be emphasized
following major results that reflect the personal contribution of the applicant in the
development of these problems:
Chapter 1 1. Approach to the analysis of forecasting models allowing for the development of an
innovative economy. 2. Identification of key features of the prediction to control the next
generation technology changing.
Chapter 2 1. Models for the expert network formation and evaluation, taking into account the
particular expertise in the rapidly changing highly integrated system of mass technologies. 2.
Models for forecasting (models to identify complexes of objects and properties that preserve the
consistency of the improving process and support the prediction.)
Chapter 3 1. Plan of scientific-technological areas monitoring.
Chapter 4 1. Results of developed models applying to analyze the data obtained in the
monitoring.
The practical significance of the thesis is as follows:
1) methodological framework and tools to predict the direction of new generation sciencetechnology was created;
2) earned results let to form effective expert network;
3) to develop a set of informational materials (based on monitoring) for control of innovation
development of technological platforms process;
4) developed methods for network of experts evaluating can optimize the process of formation of
several industry forecasting centers.
Testing work. The main provisions of the thesis presented at scientific conferences in NIYU
MIFI. Results of the thesis are reflected in two publications in journals from the WAC list; in
two research reports conducted by NIYU MIFI for the Ministry of Science and Education.
Thesis structure. The thesis consists of an introduction, four chapters and a bibliography.
Thesis content.
The first chapter discusses the features of the processes of modern techno-economic systems.
Shown as a mass technology is beginning to control the direction of many other technologies
improving. In this case, the barriers of individual technologies development are removed by
rapid technological progress of the system.
The main problem is in the fact that as a consequence of high growth, wrong decisions based on
the prediction, quickly secured the properties of systems. It would be extremely difficult to
correct them. Therefore, rapid changes must be agreed by nature, but not by results, and not by
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appearances. It’s necessary to define models, showing consistency of reasons for changes. These
prediction models are closely related to models used for decision-making [1,2].
Chapter 1 also identified the dominant analysis problems.
1. With high integration and rapid changes had substantial difficulties in applying statistical
methods and expertise.
2. The reality is "running away" from the older models. The collected statistics quickly become
obsolete. The number of parameters required for the evaluation increases. In a changing market
the level of responsibility for provided statistical information decreases.
3. Application of known expert research techniques begins to meet significant challenges. In
particular: the high rate of change leads to experts disorientation. Large amounts of new
knowledge and circumstances do not have time to properly comprehend. The experts have not
yet accumulated the experience of thinking in a new class of models.
4. "Tuning" procedures of analytical models by predicting results are not keeping pace with
reality changes. The models always remain inadequate. Errors are accumulating.
In Chapter 2, the dominant methodological problems were identified and prediction models
were developed.
It’s necessary to reveal the structure of technology relations in development for dynamic models
creating.
Initially was used the method of "challenges and parries." However, this scheme describes well
only simple techno-economic systems. With increasing complexity, it loses its effectiveness, for
example, because of the feedback.
The main "challenge" is the growth of "complexity", i.e. the need to move to new analytical
methods.
To remove the increasing complexity in these tasks need to use models that secure stable
relationship, supporting dynamics. Address some of the basic models.
In section 2.1 a formation method and evaluation criteria of the expert network were suggested.
During the formation of experts network specialists, whose competence could be agreed (expert
cluster) need to be invited. If the competence of experts is too close, their views on the processes
in the system will be "one-sided". If competence is too different, the assessment will be poorly
integrated.
For consistency of opinions, the experts need to be combined by the composition of columns in
which they work, by the activity of their work in the following categories (for example, by the
number of publications, participation in R & D, etc.). For example, in the article [1], the author
considers the thesis example of experts network building for the subject of "Radioactive Waste
Management (RWM)" is shown.
In Chapter 2, it was suggested by the author that the creation of structures related in
supporting innovative development should be predicted.
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In the remaining sections of Chapter 2 the models for technical and economic structures
of the system allocation, supporting the natural development of consistent processes are
described. In particular, given the basic model of the innovative facility, a model of the
innovation process in the consumer environment, the model of the innovation process in the
processing facility, etc. These models are described by the author in the article [2]. Assessment
indicator of the predicted structure's innovative potential was proposed, which was described by
the author in the article [3]
In Chapter 3, a monitoring program of the three sectors of scientific and technical
direction was developed and monitored. There are economic, social, scientific and technological
development trends defined. Dominant parameters and ways of food production systems and
technologies improving were determined. The most promising products and technologies were
identified, and the relevant production facilities in Russia as well. For the analysis and prediction
models developed in Chapter 2 were applied. The variants of the development strategy of
discussed sectors of scientific-technological areas were offered.
Chapter 4 proposes and describes forming system of complex of information products
based on the results of monitoring. It was created as a control tool of innovation development
processes in the businesses and organizations complex. System of information development and
distribution was proposed.
Paper concludes with recommendations on the use of work's results.
Thesis results were used for the research work: "Building of network of sectoral
prediction centers of scientific-technological development in the leading Russian universities by
"Energy efficiency and conservation" priority. Ref: 2011-2.1-521-014-005".
Of the thesis presented in the following publications:
1. Publications in journals included in the list of VAK RF:
1) Formation and evaluation expert network for prediction of innovative scientific and
technological direction;
2) Indicator for prediction of science - technology trends prediction;
3) Feature prediction research and technological development in economics of
innovation.
2. Presentations at international conferences.
1. XV International Telecommunication Conference of Young Scientists and Students “Youth
and Science” Part, page, “Study of the LED industry products"
2. XVI International Telecommunication Conference of Young Scientists and Students “Youth
and Science” Part, page, “Evaluation model of innovative structure formation in high school”