A Novel Median Dendritic Neuron Model for Prediction

A Novel Median Dendritic Neuron Model for Prediction

Blog Article

Dendritic neuron model (DNM) that utilizes a single dendritic neuron to emulate the information processing in human brains has been successfully applied to classification, approximation, and prediction fields.However, it is still a challenging task to improve the performance for forecasting the time series with outliers.A time series is a collection of data Collections ordered in time.An outlier in time series as an input can affect prediction performance.Thus, in this study, we first propose a novel median dendritic neuron model (MDNM) for prediction to deal with time series with outliers.

In MDNM, DNM and median function B-3 are combined to achieve better forecasting results.Moreover, states of matter search (SMS) algorithm is used to train MDNM.Twenty real time series and a benchmark time series are adopted to verify the performance of MDNM.The comparison between the MDNM and DNM suggests that MDNM is effective for forecasting time series with outliers.