摘要
以模糊数学和决策理论为基础,通过建立成像数据模糊指数函数及平方误差模糊指数函数,提出了一种称为模糊多目标优化的新的算法模型,对成像数据的噪声进行抑制实现数据优化.实验结果表明,所提出的模糊多目标优化算法模型有较强的抑制噪声能力,理论和实验有较好的一致性.
In this paper, the author develops a new algorithm model named Fuzzy Multicriterion Optimization Algorithm Model ( FMOAM) for reduced noise and optimizing imaging data. The model is structured based on the theories of fuzzy mathematics and decision - making via the method of deducing imaging data fuzzy exponent function and square error fuzzy exponent function. The expenment results indicate that the FMOAM in this paper has better consistency with the theory and expenment as well as obvious advantage of antinoise ability.
出处
《后勤工程学院学报》
2005年第1期41-44,共4页
Journal of Logistical Engineering University
关键词
成像数据
噪声
模糊指数函数
多目标优化
算法
imaging data
noise
fuzzy exponent function
multicriterion optimization
algorithm
