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本文基于可逆马尔柯夫链理论探讨了有关沉积序列中的循环类型定量分析的问题。前人提出的几种方法都有一个共同的不足点,即在整个序列中只找出一种可能的旋回,且对旋回类型的判别带有较大的主观随意性。本文提出的新方法能够通过分解和比较一个序列中所有可能存在的旋回类型找出最可能的沉积趋势。通过实例研究说明了新方法的具体算法和实际效果。
Based on the reversible Markov chain theory, this paper discusses the quantitative analysis of cyclic types in sedimentary sequences. Several methods proposed by the predecessors all have a common deficiency, that is, only one possible cycle is found in the entire sequence, and the subjective and arbitrary judgment of the cycle type is large. The new method proposed in this paper can find out the most likely deposition trend by decomposing and comparing all possible gyration types in a sequence. The case study illustrates the specific algorithms and practical effects of the new method.