摘要
蒙特卡罗法采用统计抽样理论近似求解工程问题,但其存在着模型精确度和时间复杂度相互矛盾的问题。通过估算圆周率,构建Monte-Carlo法实验模型,对模型的精确度和时间复杂度进行了理论分析,提出了两种基于实验模型的改进方案,并采用移位和预处理的思想,将大数除法转化为乘法来降低计算复杂度,从而提高梅森算法效率。仿真结果表明,在保持相同精确度的情况下,改进型的实验模型和算法能够大幅度降低仿真时间,提高仿真速度,具有一定的工程应用价值。
Monte Carlo method uses statistical sampling theory approximation for solving engineering problems. There are the conflicting issues of model accuracy and time complexity, so experimental model of the Monte-Carlo method was established to estimate pi and theoretically analyze the model accuracy and time complexity. This paper put forward the idea of two improvement program based on the experimental model, and through shift and pretreatment, converted the Tarsus division to reduce the computational complexity of multiplication Mason algorithm to improve efficiency. The simulation results show that in the case of maintaining the same accuracy, the improved experimental model and algo- rithms can significantly reduce the simulation time, improve the simulation speed, and thus possess a certain value in en- gineering.
出处
《计算机科学》
CSCD
北大核心
2014年第1期293-296,共4页
Computer Science
基金
教育部人文社会科学研究青年基金项目(11YJC6302620)
中国博士后基金项目(2012 M511845)
国家固态酿造工程技术研究中心项目(GCKF201102)资助
