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(4) construction of theoretical distribution of probabilities with its assessment by
one of the statistical criteria;
(5) calculation of characteristics for the procedure of adopting hypotheses by the
Neyman-Pearson classical method with the resulting assessment of the pro-
cedure by the current volume of samples;
(6) calculation of characteristics of the procedure of successive analysis and
visualization of its state;
(7)
realization of the functions of the operator
'
s access to the system
'
s units at any
s functioning with possibilities to make resolves on
changing the parameters of the procedure or ceasing measurements; and
(8) visualization of the resolves.
step of the system
'
This set of units ensures the formation of the model of the measurement pro-
cedure depending on the a-priori information about the parameters and the character
of the process under study. At the same time, the operator is able to test the
accuracy of the input information and promptly change the strategy of monitoring.
On the whole, the set of the indicated units is an automated system for making
statistical decisions.
Moberg (2006) considered environmental systems analysis (ESA) tools as a
quantitative and multidisciplinary research
field aimed at combining, interpreting
and communicating knowledge from the natural and social sciences and technology.
In other words, ESA delivers methods and tools for the environmental assessment of
human
made systems using a systems perspective. Between the tools that are most
frequently used, Moberg (2006) indicated on the following tools:
‐
SEA (Strategic Environmental Assessment) that is a procedural tool for han-
dling environmental (and sustainability) aspects in strategic decision
‐
making
(policies, programmes and plans); and
EIA (Environmental Impact Assessment) that is a procedural tool required by
law in some situations and that describes the environmental impact of a sug-
gested project and its alternatives (e.g., the construction and localization of a
waste incineration plant).
In general, not only these but also other tools play a crucial role in managing and
minimizing the risk and the uncertainty arising because of the environmental decision
making procedures. Uncertainty, which may be both scienti
cally and socially based,
is a typical feature of decision-making processes. Speci
cally, environmental
decisions are complex, since environment comprises many components, numerous
processes, complex interconnections and feedback mechanisms. Uncertainty concept
has different forms and kinds. The main problem of environmental decision-making is
how the uncertainty can be reduced. This chapter describes constructive algorithms
and methods as a solution to this problem.
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