<正> To process the data with strong historical features, such as data in earthquake research,weather forecast, medical records and census, a new mathematical model of historical datasystem is proposed. This mod...<正> To process the data with strong historical features, such as data in earthquake research,weather forecast, medical records and census, a new mathematical model of historical datasystem is proposed. This model can be characterized as ' relational database with timemark + histotical rule base = historical database', and it is easy to implement. The formaldescription of historical database and a special class of historical rules-premonitory de-pendency (abbreviated as PD)-are discussed, the poperties and inference axioms of PDare investigated. The soundness and completeness of the axioms are proved. The problemsabout the true-set of historical rules, such as the problems of emptyness, infiniteness,equivalence and containment are proved to be undecidable.展开更多
基金Project supported by the National Natural Science Foundation of China.
文摘<正> To process the data with strong historical features, such as data in earthquake research,weather forecast, medical records and census, a new mathematical model of historical datasystem is proposed. This model can be characterized as ' relational database with timemark + histotical rule base = historical database', and it is easy to implement. The formaldescription of historical database and a special class of historical rules-premonitory de-pendency (abbreviated as PD)-are discussed, the poperties and inference axioms of PDare investigated. The soundness and completeness of the axioms are proved. The problemsabout the true-set of historical rules, such as the problems of emptyness, infiniteness,equivalence and containment are proved to be undecidable.
