In water bloom prevention and control

water bloom prediction is always a difficult problem. This paper proposes a new water bloom prediction method based on multiple characteristic factors time series analysis to take into account the integrated effect of multiple characteristic factors along with the periodicity and random effect of environmental variables

to solve the problem that existing bloom prediction is not accurate enough

and to analyze the correlation between influential factors and water bloom.A multidimensional hidden periodic-auto regression (MHPAR) model is put forward based on the characteristic factors time series.A water bloom prediction method and an influential factors analysis method are put forward by using multidimensional period stationary time series analysis.Comparing the proposed model with other traditional time series models

such as auto regression (AR) model

hidden periodic-auto regression (HPAR) model and multidimensional auto regression (MAR) model

it has been found that multidimensional hidden periodic-auto regression model is useful and accurate for establishing multiple characteristic factors time series of water bloom.