Updates to the Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin are described. SHIPS combines climatological, persistence, and synoptic predictors to forecast intensity changes using a multiple regression technique. The original version of the model was developed for the Atlantic basin and was run in near–real time at the Hurricane Research Division beginning in ...

in this paper semi-markov models are used to forecast the triple dimensions of next earthquake occurrences. each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. semi-markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. in semi-markov models each zone can be considered as a state...

The method of model fitting, or adjoint method, is applied to a barotropic hurricane track forecast model described by DeMaria and Jones using a large sample of forecast cases. The sample includes all Atlantic tropical cyclones that reached hurricane intensity during the 1989–93 hurricane seasons (141 72-h forecasts of 17 storms). The cases considered by DeMaria and Jones are a subset of the pr...

Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It sho...

in recent years, various time series models have been proposed for financial markets forecasting. in each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. many researchers have compared different time series models together in order to determine more efficient ...

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components ...