techniques to model the properties of a global mean temperature dataset in order to develop a parsimonious forecasting model for … non-seasonal unit root testing with and without structural breaks, as well as ARIMA and GARCH modelling. A forecasting …

-effective pollution reduction. One of the important design questions in a trading program is how to initially distribute the emissions …

of air pollution. Chapter 2 analyses the potential application of desalination in China from an economic perspective … health impacts from air pollution in Tianjin. Although China has made dramatic economic progress in recent years, air … pollution continues to be the most visible environmental problem and imposes significant health and economic costs on society …

.Behavioral modeling is a computationally challenging problem--real world data sets can contain on the order of 10^30,000 possible … behaviors in any given situation. This work presents several scalable frameworks for modeling and forecasting agent behavior …, particularly in the realm of international security dynamics. A probabilistic logic formalism for modeling and forecasting behavior …

recommend that the Agency adopt this composite forecasting method, that uses time series analysis and current National …

overview of the models, empirical tests on real world data will be performed to determine the forecasting performance of such a …Time series forecasting is an important area of forecasting in which past observations of the same variable are … models, autoregressive (AR) techniques, moving averages (MA) etc. Recent research activities in forecasting also suggested …

This paper provides a significant numerical evidence for out-of-sample forecasting ability of linear Gaussian interest …