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...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.展开更多
A brand new expert system for earthquake prediction, called ESEP3.0, was successfully developed recently, in which the fuzzy technology and neural network conception were incorporated and the steering inference mechan...A brand new expert system for earthquake prediction, called ESEP3.0, was successfully developed recently, in which the fuzzy technology and neural network conception were incorporated and the steering inference mechanism was introduced. In addition to the functions of symbol inference and explanation of the first generation of the expert system and the knowledge learning of the second generation, ESEP3.0 has stronger human-machine interaction function. It consists of knowledge edition, machine learning, steering fuzzy inference engine and synchronous explanation subsystems. In this paper, the components and the general description of the system are introduced.展开更多
文摘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.
文摘A brand new expert system for earthquake prediction, called ESEP3.0, was successfully developed recently, in which the fuzzy technology and neural network conception were incorporated and the steering inference mechanism was introduced. In addition to the functions of symbol inference and explanation of the first generation of the expert system and the knowledge learning of the second generation, ESEP3.0 has stronger human-machine interaction function. It consists of knowledge edition, machine learning, steering fuzzy inference engine and synchronous explanation subsystems. In this paper, the components and the general description of the system are introduced.
