论文部分内容阅读
马尔可夫链在当代统计数学上,占有相当重要的地位。利用马尔可夫链预测预报森林病虫害的发生发展,要利用害虫本身发生的历史状态、演变过程,计算其转移概率。通过外推法,就可以预测预报来年森林病虫害发生发展的趋势。也就是说,通过各阶转移概率后,从各状态之间的演变规律,确定来年害虫发生处在那个发生状态,就以那个状态范围的转移概率出现的最大值,作为来年森林病虫害预报的基础。
Markov chain in contemporary statistics, occupy a very important position. Using Markov chain to forecast the occurrence and development of forest pests and diseases, it is necessary to make use of the historical state and evolution of the pest itself and calculate the probability of its transition. By extrapolation, we can forecast the trend of the occurrence and development of forest pests and diseases in the coming year. That is to say, the maximum value of transition probability in that state range is taken as the basis for the prediction of forest pests and diseases in the coming year, after the transfer probability of each stage and the law of evolution between the various states are used to determine where pests occur in the coming year .