Ontology is defined as an explicit specification of a conceptualization. In this paper, an extended ontology model was constructed using description logics, which is a 5-tuples including term set, individual set, term...Ontology is defined as an explicit specification of a conceptualization. In this paper, an extended ontology model was constructed using description logics, which is a 5-tuples including term set, individual set, term definition set, instantiation assertion set and term restriction set. Based on the extended model, the issue on ontology checking was studied with the conclusion that the four kinds of term checking, including term satisfiability checking, term subsumption checking, term equivalence checking and term disjointness checking, can be reduced to the satisfiability checking, and satisfiability checking can be transformed into instantiation consistence checking.展开更多
This paper introduces the base-X notation and discusses the conversion between numbers of different bases. It also introduces the tri-value logic that is associated with the base-3 system.
This paper presents an artificial neural network, ANN, based approach for estimating short-term wholesale electricity prices using past price and demand data. The objective is to utilize the piecewise continuous na-tu...This paper presents an artificial neural network, ANN, based approach for estimating short-term wholesale electricity prices using past price and demand data. The objective is to utilize the piecewise continuous na-ture of electricity prices on the time domain by clustering the input data into time ranges where the variation trends are maintained. Due to the imprecise nature of cluster boundaries a fuzzy inference technique is em-ployed to handle data that lies at the intersections. As a necessary step in forecasting prices the anticipated electricity demand at the target time is estimated first using a separate ANN. The Australian New-South Wales electricity market data was used to test the system. The developed system shows considerable im-provement in performance compared with approaches that regard price data as a single continuous time se-ries, achieving MAPE of less than 2% for hours with steady prices and 8% for the clusters covering time pe-riods with price spikes.展开更多
基金National Natural Science Foundation ofChina(No.70 2 710 3 8)
文摘Ontology is defined as an explicit specification of a conceptualization. In this paper, an extended ontology model was constructed using description logics, which is a 5-tuples including term set, individual set, term definition set, instantiation assertion set and term restriction set. Based on the extended model, the issue on ontology checking was studied with the conclusion that the four kinds of term checking, including term satisfiability checking, term subsumption checking, term equivalence checking and term disjointness checking, can be reduced to the satisfiability checking, and satisfiability checking can be transformed into instantiation consistence checking.
文摘This paper introduces the base-X notation and discusses the conversion between numbers of different bases. It also introduces the tri-value logic that is associated with the base-3 system.
文摘This paper presents an artificial neural network, ANN, based approach for estimating short-term wholesale electricity prices using past price and demand data. The objective is to utilize the piecewise continuous na-ture of electricity prices on the time domain by clustering the input data into time ranges where the variation trends are maintained. Due to the imprecise nature of cluster boundaries a fuzzy inference technique is em-ployed to handle data that lies at the intersections. As a necessary step in forecasting prices the anticipated electricity demand at the target time is estimated first using a separate ANN. The Australian New-South Wales electricity market data was used to test the system. The developed system shows considerable im-provement in performance compared with approaches that regard price data as a single continuous time se-ries, achieving MAPE of less than 2% for hours with steady prices and 8% for the clusters covering time pe-riods with price spikes.
