为了及时准确地预报林木害虫发生量,必须加快软科学在测报中的应用。马尔科夫链(或过程)是应用广泛、理论完备的随机过程,在近代统计学中占有重要地位。近年来,马尔科夫过程广泛应用于公共事业、气象预报、统计物理、自动化控制、地质勘探等方面。由于马尔科夫链分析方法是通过状态转移概率预报未来状态的变化,所以在害虫预测预报工作中 In order to timely and accurately predict the occurrence of forest pests, it is necessary to speed up the application of soft science in measuring and reporting. Markov chain (or process) is a stochastic process with extensive application and complete theory. It occupies an important position in modern statistics. In recent years, the Markov process is widely used in public utilities, meteorological forecasts, statistical physics, automated control, geological exploration and so on. Because Markov chain analysis method predicts the change of the future state through the state transition probability, in the pest forecasting work