摘要
讨论了分配BZ 格的区间结构及其粗糙近似算子的性质 .对于分配BZ 格中任一元素a ,利用刻画必然性测度和可能性测度的模态一元算子ν和 μ ,可以得到a的粗糙近似 (ν(a) ,μ(a) ) .该文证明了对于任意给定的一个分配BZ 格 ,都可以由ν和 μ这一对近似算子诱导一个粗糙代数 .最后 ,通过实例说明必然性测度和可能性测度模态一元算子可以刻画不确定规划问题的必然最优解和可能最优解 .
In this paper, interval structure of distributive BZ lattices and properties of rough approximation operators are discussed. For any element a in distributive BZ lattices, the rough approximation ( ν(a),μ(a ))of a is obtained by using two modal like unary operators ν and μ ( ν for necessity and μ for possibility). It is proved that a rough algebra can be induced from a distributive BZ lattice by means of rough operator pair denoted by ( ν,μ ). Finally, necessary optimal solutions and possibly optimal solutions of uncertain programming are characterized by modal like unary operators which is called necessity and possibility measures, respectively, an illustrative example is given.
出处
《计算机学报》
EI
CSCD
北大核心
2003年第9期1130-1136,共7页
Chinese Journal of Computers
基金
国家自然科学基金 ( 69972 0 6)
陕西省自然科学基金 ( 2 0 0 1SL0 8)资助
关键词
粗糙集理论
机器学习
知识获取
分配BZ-格
粗糙近似
distributive BZ lattices
modal like unary operators
rough approximation
rough algebras
