Statistical forecasts of Atlantic basin seasonal hurricane activity have been issued since 1984 by the Tropical Meteorology Project at Colorado State University (CSU) headed by William Gray. Since these initial forecasts were developed, considerable improvements in data and statistical techniques have led to improved amounts of skill in both hindcasting and forecasting of seasonal Atlantic basi...

As the increasingly fierce competition, more and more manufacturers have started to sell products through online channels apart from traditional retail channel. Meanwhile, increased competition has significantly shortened the product life cycle, which makes sales forecast meaningful. Taking lack of historical record into account, the sales forecast model based on historical sales data based on ...

Natural calamities (e.g., hurricane, excessive ice-fall) may often impede the inventory replenishment during the peak sale season. Due to the extreme situations, sales may not occur and demand may not be recorded. This study focuses on forecasting of intermittent seasonal demand by taking random demand with a proportion of zero values in the peak sale season. Demand pattern for a regular time i...

the present research was planned to evaluate the skill of linear stochastic models known as arima and multiplicative seasonal autoregressive integrated moving average (sarima) model in the quantitative forecasting of the standard runoff index (sri) in karkheh basin. to this end, sri was computed in monthly and seasonal time scales in 10 hydrometric stations in 1974-75 to 2012-13 period of time ...

This chapter deals with seasonal time series in economics and it reviews models that can be used to forecast out-of-sample data. Some of the key properties of seasonal time series are reviewed, and various empirical examples are given for illustration. The potential limitations to seasonal adjustment are reviewed. The chapter further addresses a few basic models like the deterministic seasonali...

The least square support vector machines (LSSSVM) model is a novel forecasting approach and has been successfully used to solve time series problems. However, the applications of LSSVM model in a seasonal time series forecasting has not been widely investigated. This study aims at developing a LSSVM model to forecast seasonal time series data. To assess the effectiveness of this model, the airl...

â â â  in this study, ability and skill of the nesting version of the regcm3 regional climate model in simulation of monthly and seasonal amount of precipitation and temperature using four different cumulus parameterization of grell-as, grell-fc, emanuel and kuo have been studied over khorasan area including three provinces of north khorasan, khorasan razavi and south khorasan. in this regards,...

Now-a-days, different sectors of the economy are being significantly affected by the electricity variable. In this research, we analyzed the monthly electricity consumption in Pakistan for the period of January 1990 through December 2011, using linear and non linear modeling techniques. They include ARIMA, Seasonal ARIMA (SARIMA) and ARCH/GARCH models. Electricity consumption model reveals a si...

We approach the problem of adaptively combining the predictions of an ensemble of seasonal climate models as a Multi-task Learning (MTL) problem. Unlike the traditional MTL setting, we only have a single functional task (combining the predictions ensemble members), where we consider multiple forecast periods from the same suite of models as our multiple learning tasks. Even though the same mode...