The forecasting method is important because it can predict phenomena in the future. The accuracy of the forecast depends on the model and the initial conditions. In addition the predictability measurement method is important can be check the accurate of forecasts. In this research is winter monsoon forecasts in Thailand by the shallow water model. The data from The Bjerknes Centre for Climate Research (BCCR) University of Bergen Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) is used. The Lyapunov exponent (LE) is the predictability measurement method for verify the efficiency of model and establish the new predictability measurement method by the time series analysis. The result to show that the new predictability measurement method by the time series analysis can be measure the efficiency of the winter monsoon forecasts in Thailand by the shallow water model for December 2015 to December 2056 are suitable.

The purpose of this research was to construct the appropriate forecasting model for the export values of alcoholic beverages using three-time series analysis methods including Box-Jenkins method damped trend exponential smoothing method and combined forecasting method. Time series data from the website of Office of Agricultural Economics with total 199 months from January 1998 to July 2014 were used and divided into two series. The first 192- month data from January 1998 until December 2013 were used to build the forecasting models and the last 7-month data from January to July 2014 were used to compare the forecasting method accuracy via the criteria of the lowest mean absolute percentage error and root mean squared error. Research findings indicated that for all forecasting methods that had been studied combined forecasting method was the most accurate method and this model was when and represent the single forecasts at time t from Box-Jenkins method and damped trend exponential smoothing method respectively.

The purpose of this research was to construct an appropriate forecasting model for the export quantity of frozen and chilled chicken using three time series analysis methods including Box-Jenkins method Holt’s exponential smoothing method and damped trend exponential smoothing method. Time series data from the website of the Office of Industrial Economics with total 130 months during January 2004 to October 2014 were used and they were divided into two series. Fristly 120 months from January 2004 to December 2013 were used to build the forecasting models and lastly 10 months from January until October 2014 were used to compare the forecasting methods accuracies via the criteria of the lowest mean absolute percentage error and root mean squared error. Research findings indicated that all forecasting methods that had been studied damped trend exponential smoothing method were the most accurate method and showed the forecasting model as where m represented the number of periods to forecast ahead with the starting value was January 2014 (m = 1).

The objective of this research is to propose a forecasting model for uncertain demand index data of steel. The forecasting model proposed by Yelland (2010) was modified by adjusting the prior distributions of some parameters in the model in order that it is suitable for the demand of steel in Thailand. The algorithms for model fitting were written in OpenBUGS. The proposed model was compared to a classical exponential smoothing model. The research found that the forecast errors from the proposed forecasting model were minimum.

Corporate governance principle has played an important role in predicting the business failure because the concept of good corporate governance will result in value and value added to the business and shareholders. Several previous studies attempt to find the relationship between corporate governance mechanisms and firm’s performance. It was expected that company with good performance will not be likely to go bankrupt. However this article reviews the compiled documents and studies in the past concerning corporate governance mechanisms (board structure board committees and ownership) as application tool to predict business failures.