指出在复杂系统建模中，采用多层迭代算法估计模型的参数。
The paper proposes to use parameters of multilayer iterative algorithm estimation model for the model establishent of complex systems.
然而，数据仓库解决方案具有一些重要的不同，包括强大的面向业务的数据、进程的多层迭代以及更多终端用户的涉及。
However, the data warehouse solution has some important differences, including: a strong orientation toward business data, multi-level iteration of the process, and more end-user involvement.
在一阶马尔可夫假设下，利用多层前向神经网络进行迭代逼近求解。
The solution was put forward by the iterative approach through multiple-forward network under Markov hypothesis.
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