Introduction to Influence Diagrams
An influence diagram is a simple
illustrated representation of a visual problem. Influence diagrams
serve as mutual graphical apparatus for visualizing and scrutinizing complex
systems. Decision-making teams require a thorough comprehension of the
often-complicated network of interrelated dynamics that administrate system
behavior in order to make consistently good decisions. By graphically
representing system interaction, an influence diagram facilitates such
teams to grasp behaviors far more effortlessly than with unaided intuition.
It also presents a methodology for analyzing these interactions to gain
system insight for improved decision-making and an intuitive way to identify
and display essential elements like decisions, uncertainties, and objectives,
and how they influence each other.
Generating Influence Diagrams
Influence diagrams use shapes called nodes
and arrows called arcs, which enable the
diagram to function as a graphical representation of a system. Nodes represent
system variables while arcs represent influences
between variables. The direction of an arc is vital, as the arc
specifies that the value of the node at its head (arrow end) depends directly
on the value of the node at its tail. Nodes used to define model inputs
are known as "data" nodes and nodes that use values from other
nodes to calculate new values are called "calculation" nodes.
Figure: This diagram is
a simplified version of the actual influence diagram representing
a system of chemical process. The first model takes Temp.and Pressure,
the "data" nodes that calculate the reaction rates for
the reaction. Model 2 takes the concentrations of the reactants
and calculates their activities. Reaction Rates and Reactant Activities
are the "calculation" nodes. Using these two intermediates,
it is possible to calculate the output composition of the chemical
process, which is the "output" node
Application of Influence Diagrams
These diagrams can be applied in various areas
of analysis. These Diagrams can be applied to Sensitivity Analysis, Mathematical
Modeling, Model Fidelity, Improvement Initiatives and Quantifying risk
- It aids in understanding quantitative relationships in math model.
- Influence Diagrams divide a system into logical entities or components-
one per node- that can be a single value.
- Further on, smaller sets of calculation nodes can be selected and
tested in isolation.
- Modularity helps to maintain and upgrade Influence Diagrams easily.
- Influence Diagrams function as open windows into system understanding
rather than being black boxes.
Comparing Influence diagram and Decision tree
When compared to a decision tree, influence diagram proves as a much more
simple and compact depiction of analysis. Though the decision tree explains
more details of the potential paths or scenarios as series of branches,
this detail requires a lot of complex procedure, making it too complicated
to display. While, the influence diagram illustrates the dependencies
among variables more visibly than the decision tree.
Thus, an overall concluding aspect that can be derived is that the influence
diagram is much better than any other decision-making technique.
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