摘要
对于有序分割类,模糊判别时通常使用的最小代价准则、最大属性测度准则以及最大隶属度准则由于掩盖了介于两个隶属度之间的差别,有时可能得出并不合理的结论。首先提出了一种利用拓广优化算法综合指标权重的方法,然后基于置信度准则提出了一种改进的模糊综合评价方法,有效地避免了上述问题。最后用一个实例说明了本文方法的有效性和科学性。
For a sequential segmentation category, the principle of the lowest cost, the principle of maximum degree of measure and the principle of maximum degree of membership sometimes can get unreasonable conclusion, because they conceal the difference of two degree of membership. First of all, a new expanded optimization algorithm is presented for combining index weights, then bring out a improved fuzzy synthetic evaluation method based on reliability code. The proposed method can overcome the shortages of the traditional fuzzy synthetic evaluation. Case results clearly show that the proposed method is attractive and effective.
出处
《科学技术与工程》
2008年第8期2193-2197,共5页
Science Technology and Engineering
基金
甘肃省科技攻关项目(GS044-A52-001-24)资助
关键词
模糊综合评价
置信度准则
拓广优化算法
fuzzy synthetic evaluation reliability code expanded optimization method
