Clinical mastitis was analyzed with mixed linear models (LM) and survival analysis (SA) using data from the first 3 lactations of >200,000 Swedish Holstein cows having their first calving between 1995 and 2000. The model for both methods included fixed effects of year-month and age at calving, fixed regressions of proportions of heterosis and North American Holstein genes, and random effects of...

The strong interaction between the discrete dynamic and the one continue is now seriously taken into account in the model. These models newborn so-called hybrid models describe at one time the two dynamics and are already used as well in control systems as in analysis. The methods and present tools of the dependability of systems are either of quantitative order or qualitative one. The avenue o...

An approach for hybrid model parameter identification based on sensitivity equations approach is tested on a hybrid model for biosurfactant production process. The computer simulations were performed using software tools created in Matlab (The MathWorks, Inc.) environment. Possible difficulties and ways of practical implementation of the analyzed identification algorithms for the identification...

one of the most important and valuable goal of software development life cycle is software cost estimation or sce. during the recent years, sce has attracted the attention of researchers due to huge amount of software project requests. there have been proposed so many models using heuristic and meta-heuristic algorithms to do machine learning process for sce. cocomo81 is one of the most popular...

Innovative methods have been developed for diagnosis, activity monitoring, and state estimation that achieve high accuracy through the use of stochastic models involving hybrid discrete and continuous behaviors. A key bottleneck is the automated acquisition of these hybrid models, and recent methods have focused predominantly on Jump Markov processes and piecewise autoregressive models. In this...

Hybrid modeling seeks to address problems associated with the representation of complex systems using “single-paradigm” models: where traditional models may represent an entire system as a cellular automaton, for example, the set of submodels within a hybrid model may mix representations as diverse as individual-based models of organisms, Markov chain models, fluid dynamics models of regional o...

nowadays, due to increasing the complexity of ic engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. in this paper four network base...