electronic warfare self-protection of battlefield helicopters - Aaltodoc
electronic warfare self-protection of battlefield helicopters - Aaltodoc
electronic warfare self-protection of battlefield helicopters - Aaltodoc
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disadvantage is that understanding <strong>of</strong> the factors that have contributed to the result<br />
requires detailed mathematical insight into the problem. In order to make the<br />
problem more understandable, mathematical tools have to be supported either by<br />
drawings or by models that explain intricacies and alternatives.<br />
2.4 Conclusions on methods<br />
Conclusions <strong>of</strong> the discussion in Section 2.3 are summed up in Table 3. One<br />
conclusion drawn from the table is not to use Checkland’s SSM in the present work.<br />
Further, mathematical tools will be used, if needed, only in a supportive role.<br />
Qualitative methods will be preferred over quantitative methods, but simulation will<br />
be used if a specific advantage can be expected from it. As mentioned in Section<br />
2.3.7, FSD is the only simulation tool that has been considered. The main reason for<br />
this choice is that the results <strong>of</strong> the present work are intended for use in a multitude<br />
<strong>of</strong> situations, and for communication with people <strong>of</strong> different backgrounds, and the<br />
methods should be kept at the simplest possible level. Figure 7 shows that data flow<br />
diagrams and CLDs can be used to model similar processes or systems. Since CLDs<br />
are less well known in the engineering community the decision is mainly to build<br />
qualitative models using DFDs. The bulk <strong>of</strong> the information in this study will be<br />
presented through the “traditional methods”, but the extent to which they are useful<br />
for presenting the holistic view on EWSP <strong>of</strong> <strong>battlefield</strong> <strong>helicopters</strong> must be judged<br />
when discussing the entire work.<br />
Section Conclusion<br />
2.3.1<br />
and<br />
2.3.2<br />
Quantitative methods (simulations) are preferable when access to numerical data is<br />
painless and the data is reliable, qualitative methods (modeling) are to be preferred for<br />
unstructured problems and when data is not available. In equivocal cases the continuum <strong>of</strong><br />
OR methods (Figure 5) can be a guide.<br />
2.3.3 No single alternative presented in Table 1 can be assessed to satisfy the requirements alone<br />
for forming a holistic view on EWSP.<br />
2.3.4 The “traditional methods” are “traditional” because <strong>of</strong> their inherent strengths; hence they<br />
maintain their position in many forms <strong>of</strong> communication. The major weakness is the<br />
demand that textual information puts on participants.<br />
2.3.5 Despite differences both DFDs and CLDs are possible modeling tools for the present<br />
work. The resemblance between the DFD and CLD raises the question <strong>of</strong> what changes are<br />
needed to use DFDs in connection with FSD models instead <strong>of</strong> CLDs.<br />
2.3.6 Checkland’s SSM has merits in facilitating group discussions on unstructured problems,<br />
but application <strong>of</strong> Checkland’s SSM to the present work would shift the focus from EWSP<br />
to SSM methodology.<br />
2.3.7 FSD is intended for simulation <strong>of</strong> general systems, and is as such applicable to a wide<br />
range <strong>of</strong> problems. It has inherent limitations that could be a problem for the present work,<br />
but these do not seem serious enough to discourage from using the methodology.<br />
Validation <strong>of</strong> simulations—regardless <strong>of</strong> the type <strong>of</strong> simulation—cannot be carried out to<br />
objective completeness, but will ultimately rest on faith.<br />
2.3.8 Understanding <strong>of</strong> factors governing the results <strong>of</strong> mathematical tools requires familiarity<br />
with governing physical principles, which is an obstacle in many situations. Mathematical<br />
tools can, however, be useful in an auxiliary role.<br />
Table 3: Conclusions drawn from the discussion in Section 2.3.