in this paper, we present a multi-formalism modeling framework (abbreviated by mfmf) for modeling and simulation. the proposed framework is defined based on the concepts of meta-models and uses object-orientation to overcome the complexities and to enhance the extensibility. the framework can be used as a basis for modeling by various formalisms and to support model composition in a unified man...

This paper takes a Bayesian-decision theoretic approach to transfer function estimation, nominal model estimation, and quantification of the resulting model error. Consistency of the nonparametric estimate of the transfer function is proved together with a rate of convergence. The required quantities can be computed routinely using reversible jump Markov chain Monte Carlo methods. The proposed ...

A recent perspective on model error modeling is applied to set membership identification techniques in order to highlight the separation between unmodeled dynamics and noise. Model validation issues are also easily addressed in the proposed framework. The computation of the minimum noise bound for which a nominal model is not falsified by i/o data, can be used as a rationale for selecting an ap...

experimental determination of solubility and ternary phase diagram of chiral compound are of tedious and time consuming tasks, and in many cases, there is not enough experimental data for different enantiomeric compositions to access the experimental ternary phase diagram. using thermodynamic models with predictive capability, having less dependency on experimental data, affords a great advanta...

the decisions made in the planning phase of a building project greatly affect its future operation and maintenance (o&m;) cost. recognizing the o&m; cost of condominiums’ common facilities as a critical issue for home owners, this research aims to develop an artificial neural network (ann) o&m; cost prediction model to assist developers and architects in effectively assessing the impacts of the...

Flooding is one of the most occurring natural hazards every year risking the lives and properties of the affected communities, especially in Philippine context. To visualize the extent and mitigate the impacts of flood hazard in Malingon River in Valencia City, Bukidnon, this paper presents the combination of Geographic Information System, high-resolution Digital Elevation Model, land cover, so...

The aim of this paper is robust identification of smart foam, as an electroacoustic transducer, considering unmodeled dynamics due to nonlinearities in behaviour at low frequencies and measurement noise at high frequencies as existent uncertainties. Set membership estimation combined with model error modelling technique is used where the approach is based on worst case scenario with unknown but...

It is difficult to build an accurate model to predict the dynamic error of CMM by analyzing error sources. An innovative modeling method based on Variance Analysis and Improved Partial Least-square regression (IPLSR) is proposed to avoid analyzing the interaction of error sources and to overcome the multi-collinearity of Ordinary Least-square regression (OLSR). Among many impact factors the mos...

Thermal errors and force-induced errors are two most significant sources of the NC grinding machine inaccuracy. And error compensation technique is an effective way to improve the manufacturing accuracy of the NC machine tools. Effective compensation relies on an accurate error model that can predict the errors exactly during machining. In this paper, a PSO–BP neural network modeling technique ...

in this paper semi-markov models are used to forecast the triple dimensions of next earthquake occurrences. each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. semi-markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. in semi-markov models each zone can be considered as a state...