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The experimental Decision Support System for Measurement of the Effect by the
Environmental Factors on the Value of Energy Companies (ESIAPVN-DS), based on the
algorithm suggested by the authors and on multiple criteria analysis, enables a more
comprehensive process for solution framing and has the following advantages:
the system helps to quickly measure the utility, priority, and value of complex objects
using contemporary methods, it helps to consider and analyse substantially more
environmental factors, and to make integrated assessments of quantitative and
qualitative indicators describing the objects in question;
the DSS measures the value based on a comprehensive analysis of the environment, and
grounds the assumptions with better accuracy; the measuring process not only shows
the final value, but also offers comprehensive interim results helpful in decision-making
at various levels (recommendations about the effect of separate environmental factors
on the value, and about the possibilities to mitigate the negative effect of the factors
thus improving the operating environment);
the system can be easily supplemented, improved and then used to frame various
solutions: to assess the impact of environmental factors, to identify the vital values of
factors, to plan the courses of action, to submit reliable information to various
institutions and, finally, to analyse the reasons behind changing value.
6. References
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Ashina, S.& Nakata, T. (2008). Quantitative analysis of energy-efficiency strategy on CO 2
emissions in the residential sector in Japan - Case study of Iwate prefecture. Applied
Energy, Vol.85, No.4, (April 2008), p.p. 204-217, ISSN 0306-2619
Benavides, J. A. C. & Prado J. C. (2002). Creating an Expert System for Detailed Scheduling.
International Journal of Operations & Production Management , Vol.22, No.7, p.p. 806-
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Bertin, J. (1983). Semiology of Graphics . Madison, WI: University of Wisconsin Press, ISBN
0299090604
Booty, W. & Wong, I. (2010). Case Studies of Canadian Environmental Decision Support
Systems. Decision Support Systems, INTECH, Olajnica 19/2, 32000 Vukovar, Croatia,
ISBN 978-953-7619-64-0, Available from <www.sciyo.com>
Brans. J.P. & Mareschal, B. (2005). PROMETHEE methods, in: Figueira, J., Greco, S., Ehrgott,
M. (Eds.), Chapter 5. Multiple CriteriaDecision Analysis: State of the Art Surveys .
Springer, , p.p. 163-195, ISBN 978-0-387-23067-2
Brito, A. J. & Almeida, A. T. (2008). Multi-attribute risk assessment for risk ranking of
natural gas pipelines, Reliability Engineering & System Safety, Vol.94, No.2, (February
2009), p.p. 187-198, ISSN 0951-8320
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