The development of modeling tools and advanced environments has resulted in great benefits to the community at large. The incorporation of AI tools into system dynamics presents opportunities for expanding on c
Buck, J., Tanchoco, J., and Sweet, A., Parameter estimation methods for discrete exponential learning curve, AIIE Trans., 8, 185-194, 1976.J.R. Buck, J.M.A. Tanchoco and A.L. Sweet, Parameter estimation methods for discrete exponential learning curves, AIIE Trans. 8, no. 2 (...
Parameter Uncertainty and Estimation Model parameter estimation represents a challenge in many fields. A large number of algorithms exist to address this need. These run the gamut from straightforward steepest descent methods, to genetic algorithms, simulated annealing, regression, Bayesian methods and oth...
estimates the state-space model with additional options specified by one or moreName,Valuepair arguments. For example, you can specify to deflate the observations by a linear regression using predictor data, control how the results appear in the Command Window, and indicate which estimation method ...
The reliable solution of nonlinear parameter estimation problems is an important computational problem in the modeling of vapor–liquid equilibrium (VLE). Conventional solution methods may not be reliable since they do not guarantee convergence to the global optimum sought in the parameter estimation prob...
additional options specified by one or moreName,Valuepair arguments. For example, you can specify to deflate the observations by a linear regression using predictor data, control how the results appear in the Command Window, and indicate which estimation method to use for the parameter covariance ...
We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter ...
Parameter estimation based on truncated data is dealt with; the data are assumed to obey truncated exponential distributions with a variety of truncation time—a 1 data are obtained by truncation time b 1, a 2 data are obtained by truncation time b 2 and so on, whereas the underlying distrib...
Therefore, synchrophasor-based data are not suitable for HFO parameter estimation. On the other hand, various methods have been developed using waveform-based data. A comprehensive synchronized measurement system can effectively detect SSO in12, but the measurement delay exceeds 1 s, leading to a...
In this paper, we describe a Python software package that has been developed for model-based parameter estimation, while focusing on the characterization of the uncertainties associated with the estimates. Existing work in this area has often focused on methods for improving the optimal point ...