Sentence examples for evaluating and forecasting from inspiring English sources

The performance of neural networks in evaluating and forecasting banking crises have been examined in this paper.

The second part characterises the multiagent system MWING, a software solution that by conducting active measurements collects data necessary for analysing, evaluating and forecasting Web applications performance.

Consequently, it has been seen that artificial neural networks which are capable of producing successful solutions for semi-structural and non-structural problems, can be used effectively in evaluating and forecasting banking crises.

We illustrate how evaluations of decision process reconstructions could potentially improve our understanding of future archival needs by simultaneously documenting, preserving and reconstructing computer-assisted decision processes, and evaluating and forecasting computational and storage requirements of the documentation and reconstruction processes over time.

Examples included laboratory studies of UV exposure, population studies that examined resilience after extreme weather events, ecological studies that examined the biology of pathogens and vectors in the field, and modeling efforts that focused on evaluating and forecasting disease risk.

The researchers record, evaluate and forecast management-induced changes of this agrarian ecosystem and its environment.

The framework demonstrates the dynamic linkage of project management success in successive lifecycle stages and phases, and thus can be used to evaluate and forecast the likelihood of success of biomass energy projects progressively over their lifecycle.

We have, however, devised a new approach to forecasting evaluation, a predictive error-forecasting model which compares and evaluates forecasting methods based on their factor levels when faced with intermittent demand.

We present the merits of information measures for describing and forecasting molecular variation within and among groups, comparing forecasts with data, and evaluating underlying processes such as dispersal.

The predictive value of the SET-I data was evaluated for forecasting an injury later on by analysis of horse and pony data using a logistic-regression with injury as a dependent variable, and age, sex, and horse/pony interactions as independent variables.

Moreover, only the computation times for training and evaluating the forecasting models are of interest in the present contribution.