The China Coastal Bulk Coal Freight Index (CBCFI) is the main indicator tracking coal shipping price volatility in Chinese market. This index indicates variable performance of current status and trends coastal sector. It critical for government companies to formulate timely policies measures. After investigating fluctuation patterns external factors light forecasting accuracy requirements CBCFI...

A method for obtaining the colored noise gain function is proposed. The which gives auto-covariance of output signal SISO (single input and single system) from singnal. asumed to be white or Gausian noise. And ACF(auto-covariance function) ARMA (autoregressive moving average) model derived proposed with in closed form. Some results calculation ACF simulation system show effectiveness method.

BACKGROUND Car accidents are currently a social issue globally because they result in the deaths of many people. The aim of this study was to examine traffic accidents in suburban Tehran and forecast the number of future accidents using a time-series model. METHODS The sample population of this cross-sectional study was all traffic accidents that caused death and physical injuries in suburban...

The monsoon rainfall has very important affect on the agricultural production, livestock as well as human ecology. In this study, try to fit Artificial Neural Network (ANN) model to predict average monsoon rainfall. For the ANN models monthly average rainfall, sea surface temperature, wind speed, monsoon rainfall, temperature is used as inputs to predict the monsoon rainfall. The feed forward n...

There has been increased interest in time series data mining recently. In some cases, approaches of real-time segmenting time series are necessary in time series similarity search and data mining, and this is the focus of this paper. A real-time iterative algorithm that is based on time series prediction is proposed in this paper. Proposed algorithm consists of three modular steps. (1) Modeling...

In this paper two popular time series prediction methods – the Auto Regression Moving Average (ARMA) and the multilayer perceptron (MLP) – are compared while forecasting seven real world economical time series. It is shown that the prediction accuracy of both methods is poor in ill-structured problems. In the well-structured cases, when prediction accuracy is high, the MLP predicts better provi...