Novel algorithm of backward cloud model without certainty
Juntao Li · Jisuanji yingyong yanjiu · 2013
The essential influence on the atomized feature of cloud model was indefinite and the error of backward cloud model without certainty was larger.To solve these problems,it demonstrated that the standard deviation of cloud drop quantitative data determined the atomized property of cloud model by the mathematical analysis of forward cloud model.The ratio of entropy to hyper entropy,named atomized factor,can measure the disperse degree of cloud drops.The analysis and experimental results reveal that the range of atomized factor corresponding to cloud distribution is 3~18,cloud distribution becomes normal distribution and backward cloud models without certainty are ineffective when the atomized factor is larger than 18.On this basis,it proved a novel algorithm of backward cloud model without certainty by the property of the fourth moment of cloud distribution.The comparative experiments with the different atomized factors and cloud drop numbers indicate that the proposed algorithm is superior to other algorithms in accuracy and stability.