模式识别与人工智能
模式識彆與人工智能
모식식별여인공지능
Moshi Shibie yu Rengong Zhineng
2013年
8期
777-786
,共10页
模糊格%粒计算%超盒粒%模糊包含关系
模糊格%粒計算%超盒粒%模糊包含關繫
모호격%립계산%초합립%모호포함관계
Fuzzy Lattice%Granular Computing%Hyperbox Granule%Fuzzy Inclusion Relation
粒的表示、粒之间的关系和运算是粒计算的主要研究内容。利用向量表示超盒粒,分析向量之间的偏序关系和超盒粒之间的偏序关系的不一致性,并引入保序函数消除该不一致性。利用格和其对偶格之间的非线性正评价函数和保序函数构造超盒粒之间模糊包含关系。为得到不同粒度的粒,设计超盒粒之间的合并算子和分解算子,证明由超盒粒集、超盒粒之间的模糊包含关系、合并算子、分解算子构成的代数系统是模糊格,构造基于模糊格的超盒粒计算分类器。用机器学习数据集中的分类问题,验证该分类器具有和模糊格推理分类器相同的推广能力并减少超盒粒的数量。
粒的錶示、粒之間的關繫和運算是粒計算的主要研究內容。利用嚮量錶示超盒粒,分析嚮量之間的偏序關繫和超盒粒之間的偏序關繫的不一緻性,併引入保序函數消除該不一緻性。利用格和其對偶格之間的非線性正評價函數和保序函數構造超盒粒之間模糊包含關繫。為得到不同粒度的粒,設計超盒粒之間的閤併算子和分解算子,證明由超盒粒集、超盒粒之間的模糊包含關繫、閤併算子、分解算子構成的代數繫統是模糊格,構造基于模糊格的超盒粒計算分類器。用機器學習數據集中的分類問題,驗證該分類器具有和模糊格推理分類器相同的推廣能力併減少超盒粒的數量。
립적표시、립지간적관계화운산시립계산적주요연구내용。이용향량표시초합립,분석향량지간적편서관계화초합립지간적편서관계적불일치성,병인입보서함수소제해불일치성。이용격화기대우격지간적비선성정평개함수화보서함수구조초합립지간모호포함관계。위득도불동립도적립,설계초합립지간적합병산자화분해산자,증명유초합립집、초합립지간적모호포함관계、합병산자、분해산자구성적대수계통시모호격,구조기우모호격적초합립계산분류기。용궤기학습수거집중적분류문제,험증해분류기구유화모호격추리분류기상동적추엄능력병감소초합립적수량。
Representation, relation and operation of granules are the main research content of granular computing. A hyperbox granule is represented by a vector including a beginning point and an end point. The inconsistency between the partial ordering relation in vector space and the partial ordering relation in hyperbox granule space is analyzed and then eliminated by the order-preserving function. The fuzzy inclusion relation between two hyperbox granules is formed by nonlinear positive valuation function and the order-preserving function between the lattice and its dual lattice. The join operator and decomposition operator between two granules are designed to achieve the granules with different granularity. The algebraic system which is composed of hyperbox granule set, fuzzy inclusion relation and the operators between two granules is proved as fuzzy lattice. Hyperbox granular computing classifiers are formed based on fuzzy lattice, and verified by classification problems on machine learning dataset. The experimental results show that hyperbox granular computing classifiers have a generalization ability comparable to that of fuzzy lattice reasoning classifiers with less number of hyperbox granules.