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Book Contents

Ch. 9
Building Model-Driven Decision Support Systems

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Modeling

A typical modeling process begins with identification of a problem and analysis of the requirements of the situation. It is advisable to analyze the scope of the problem domain and the forces and dynamics of the environment. The next step is to identify the variables for the model. The identification of variables and their relationships is very important. One should always ask if using a model is appropriate? If a model is appropriate, then one asks what variables and relationships need to be specified using an appropriate modeling tool. A solution method or method needs to be chosen. Also, analysts need to specify assumptions and make any needed forecasts. Forecasting variables or parameters is sometimes part of the construction of an MDSS. Building a MDSS also involves integrating models and other DSS components like data files and data analysis procedures. Model-Driven DSS need to be validated, evaluated and managed. Model validation is the process of comparing a model's output with the actual behavior of the phenomenon that has been modeled. Validation attempts to answer the question "Have we built the right model?"

Tasks in the Modeling Life Cycle

Task Goal Mechanism
Problem Identification Clear, precise problem statement Argumentation process
Model creation Statement of the model (s) required to mathematically describe the problem Formulation 
Integration
Model selection and modification (if necessary)
Composition
Model implementation Computer executable statement
of the model
Ad hoc program development
Use of high-level specialized languages
Use of specialized model generator programs
Model validation Feedback from validator Symbolic analysis of attributes such as dimensions and units syntax rules
Model solution Feedback from solver Solver binding and execution
Solver sequencing and control script execution
Model interpretation Model comprehension
Model debugging
Model results analysis
Structural analysis
Sensitivity analysis
Model maintenance Revise problem statement and/or model to reflect changes/insight Symbolic propagation of structural changes
Model versions/security Maintain correct and consistent versions of models.
Ensure authority to access.
Versioning
Access control methods

from Krishnan, R. and K. Chari "Model Management: Survey, Future Research Directions and a Bibliography," Interactive Transactions of ORMS, Vol. 3, No. 1, 2000. (URL http://www.coba.usf.edu/departments/isds/faculty/chari/model/doc.html)

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