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Knowledge Representation for the Geometrical Shapes

Knowledge Representation for the Geometrical Shapes
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摘要 This paper outlines the necessity of the knowledge representation for the geometrical shapes (KRGS). We advocate that KRGS for being powerful must contain at least three major components, namely (1) fuzzy logic scheme; (2) the machine learning technique; and (3) an integrated algebraic and logical reasoning. After arguing the need for using fuzzy expressions in spatial reasoning, then inducing the spatial graph generalized and maximal common part of the expressions is discussed. Finally, the integration of approximate references into spatial reasoning using absolute measurements is outlined. The integration here means that the satisfiability of a fuzzy spatial expression is conducted by both logical and algebraic reasoning.
出处 《Journal of Mathematics and System Science》 2018年第3期77-83,共7页 数学和系统科学(英文版)
关键词 Knowledge representation integrated algebraic and logical fuzzy logic reasoning machine learning. 知识表示 几何形状 模糊逻辑 空间推理 主要部件 学习技术 逻辑推理 可满足性
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