Forecasting occurrences of activities

Applying Semi-Markov Models for forecasting the Triple Dimensions of Next Earthquake Occurrences: with Case Study in Iran Area

  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 sta...

A new probability density function in earthquake occurrences

Although knowing the time of the occurrence of the earthquakes is vital and helpful, unfortunately it is still unpredictable. By the way there is an urgent need to find a method to foresee this catastrophic event. There are a lot of methods for forecasting the time of earthquake occurrence. Another method for predicting that is to know probability density function of time interval between earth...

Effect of Source Areas Anthropogenic Activities on Dust Storm Occurrences in the Western Parts of Iran

A novel grey–fuzzy–Markov and pattern recognition model for industrial accident forecasting

Industrial forecasting is a top-echelon research domain, which has over the past several years experienced highly provocative research discussions. The scope of this research domain continues to expand due to the continuous knowledge ignition motivated by scholars in the area. So, more intelligent and intellectual contributions on current research issues in the accident domain will potentially ...

Forecasting flow discharge through time series analysis using SARIMA model for drought conditions, a case study of Jamishan River

Nowadays, water supply is more limited and providing water is more difficult due to increasing population and demand for water. Thus, due to rainfall shortage and impacts of drought, the need for forecasting monthly and annual rainfall and flow discharge through time series analysis is acutely felt. One of the key assumption in time series is their static condition. However, hydrological time s...