How to assess the acceptability and credibility of simulation results
WSC '89 Proceedings of the 21st conference on Winter simulation
VV&A; I: verification, validation, and accreditation in the life cycle of models and simulations
Proceedings of the 32nd conference on Winter simulation
An integrated approach to verification, validation, and accredition of models and simulations
Proceedings of the 32nd conference on Winter simulation
Building valid models: how to build valid and credible simulation models
Proceedings of the 33nd conference on Winter simulation
Output modeling: abc's of output analysis
Proceedings of the 33nd conference on Winter simulation
Fast Discrete HMM Algorithm for On-line Handwriting Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
The Multi-Agent Data Collection in HLA-Based Simulation System
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
A knowledge-based method for the validation of military simulation
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
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According to the characteristic of randomization and sequential logic in complex simulation systems, a new evaluation method based on hidden Markov model (HMM) is presented, which applies multivariate statistical theory to quantificationally evaluate the results validity of complex simulation system. By importing matrix of observed state vector, the method enhance the clarity of describing scenario and running states of simulation systems, and ultimately implement an exploring approach to quantitative analysis for the results validity. Furthermore, quantificational evaluation criterion of results validity is given and the critical algorithm adopted in the process of quantificational evaluation is discussed in detail.