The EPC (Engineering Procurement Construction) industry is one of the most dynamic industries. problems faced are related to market conditions that often change, short construction periods, and fluctuations in material prices difficult predict. This requires an appropriate forecasting model, which can predict pattern price movements anticipate occurrence future. research aims get best during pr...

As part of the Danish contribution to MarCoast – the element of GMES (Global Monitoring for Environment and Security) Service Element Project that addresses the marine environment in Europe – DHI & GRAS have developed and are operating an operational forecast system based on numerical modelling. The models are capable of predicting a range of hydrodynamic, biological and wave phenomena up to 5 ...

The construction of a usable, formal, and extensible modeller and simulator for Smart Energy Grids is of a paramount importance in the industrial settings. Final users are interested in deploying effective smart-home configurations able to satisfy energy requests in the most economical way. Hence, a tool able to forecast both energy consumption and related costs of a smarthome configuration is ...

This study aims at modelling Nigerian total livebirths data, and to select the appropriate model for the disaggregated livebirths series among the proposed univariate stochastic time series models, based on in-sample fitting. Forecast of demographic variables such as births has a great influence on the growth of a population with respect to its demands on various systems such as education, heal...

This study describes the development of a spatio-temporal disease model based on the episodes of severe acute respiratory syndrome (SARS) that took place in Hong Kong in 2003. In contrast to conventional, deterministic modelling approaches, the model described here is predominantly spatial. It incorporates stochastic processing of environmental and social variables that interact in space and ti...