序列运算的算法复杂性分析

Algorithm Complexity Analysis of Sequence Operation Theory

序列运算理论在解决复杂不确定性问题方面已获得了大量的应用。序列运算的算法复杂性及其与其他不确定性分析方法相比较的结果,都为序列运算理论提出了值得深入研究的问题。以电力市场风险评估为例,根据序列运算与蒙特卡罗法的基本原理,分析了两者的算法复杂性,并以算例准确地比较了相同精度下2种算法的实际计算量。研究结果表明,在电力市场风险评估方面,基于序列运算理论的评估方法不仅计算量较小,并且存在相当的计算优化空间,验证了序列运算的优越性。

Sequence Operation Theory has been widely applied to solving complex uncertainty problems. Algorithm complexity of Sequence Operation, and advantages over other uncertainty analysis methods, are important theoretical problems worth in-depth researching that confront with Sequence Operation Theory. We compared Sequence Operation Theory with Monte Carlo method by a case study of power market risk assessment, and analyzed the algorithm complexity of them. Finally, we used an example to accurately compare calculating time of different risk assessment methods. The results show that Sequence Operation Theory is more efficient in power market risk assessment than traditional methods, and has considerate room for further optimization. It also verifies the superiority of Sequence Operation Theory.