摘要
Knowledge representation is a key to the building of expert systems. The performance of knowledge representation methods directly affects the intelligence level and the problem-solving ability of the system. There are various kinds of knowledge representation methods in ESEP3.0. In this paper, the authors introduce the knowledge representation methods, such as structure knowledge, seismological and precursory forecast knowledge, machine learning knowledge, synthetic prediction knowledge, knowledge to validate and verify certainty factors of anomalous evidence and support knowledge, etc. and propose a model for validation of certainty factors of anomalous evidence. The knowledge representation methods represent all kinds of earthquake prediction knowledge well.
Knowledge representation is a key to the building of expert systems. Theperformance of knowledge representation methods directly affects the intelligence level and theproblem-solving ability of the system. There are various kinds of knowledge representation methodsin ESEP3.0. In this paper, the authors introduce the knowledge representation methods, such asstructure knowledge, seismological and precursory forecast knowledge, machine learning knowledge,synthetic prediction knowledge, knowledge to validate and verify certainty factors of anomalousevidence and support knowledge, etc. and propose a model for validation of certainty factors ofanomalous evidence. The knowledge representation methods represent all kinds of earthquakeprediction knowledge well.
基金
Theprojectwasunderthe10thFiveYearKeyTechnologiesR&DProgramsofMinistryofScienceandTechnology,SubItemNo.2001BA601B010404,andtheNationalNaturalScienceFoundationofChina(60203011).
