Under aircondition,theinsitu TiCP/ Fecompositeshavebeen fabricated by a reactivecast ing route usingtheinexpensiveraw materials. The microstructuresofthecompositehavebeen studied by X ray diffraction,image analyz...Under aircondition,theinsitu TiCP/ Fecompositeshavebeen fabricated by a reactivecast ing route usingtheinexpensiveraw materials. The microstructuresofthecompositehavebeen studied by X ray diffraction,image analyzer and analyticalelectron microscopy. The me chanicalpropertiesand abrasive wearresistanceofboththeas castcompositeandthequenched composite havebeen measured. Theresultsshow thattheinsitu TiCparticles with a average sizeof 4 51μm exhibit a homogenous distribution inthe matrix, and an excellentinterface bonding between the particle and the matrix is achieved. As above microstructure features, thecomposite,especiallythequenched composite, hashigher mechanicalpropertiesand betterwear resistance,compared with high Cr whitecastiron.展开更多
This paper proposes a hybrid short-term load forecasting method,which is based on the fuzzy combination weights as well as the empirical mode decomposition process(FCW-EMD),and support vector machine optimized via the...This paper proposes a hybrid short-term load forecasting method,which is based on the fuzzy combination weights as well as the empirical mode decomposition process(FCW-EMD),and support vector machine optimized via the Bat algorithm as well as the Kalman filtering process(KF-BA-SVM).The subjective weight is presented as a new theory and is applied to capture the inherent correlation effectively among hourly loads.Based on the proposed objective weights and subjective weights,the fuzzy combination weights theory(FCW)-a new similar day selection theory is presented,which improves the accuracy of the similar day selection,and correspondingly,makes the original data for EMD processing decrease dramatically.BA is introduced to optimize parameters of the SVM model for further improving the forecasting accuracy.Using the decomposed load series via empirical model decomposition(EMD)as inputs to SVM and further correcting the output of SVM via KF,a hybrid FCW-EMD and KF-BA-SVM short-term load forecasting method is established.Numerical case studies on the load forecasting of a transformer substation in south China show that the proposed hybrid forecasting model outperforms other forecasting methods and effectively improves the prediction accuracy.展开更多
文摘Under aircondition,theinsitu TiCP/ Fecompositeshavebeen fabricated by a reactivecast ing route usingtheinexpensiveraw materials. The microstructuresofthecompositehavebeen studied by X ray diffraction,image analyzer and analyticalelectron microscopy. The me chanicalpropertiesand abrasive wearresistanceofboththeas castcompositeandthequenched composite havebeen measured. Theresultsshow thattheinsitu TiCparticles with a average sizeof 4 51μm exhibit a homogenous distribution inthe matrix, and an excellentinterface bonding between the particle and the matrix is achieved. As above microstructure features, thecomposite,especiallythequenched composite, hashigher mechanicalpropertiesand betterwear resistance,compared with high Cr whitecastiron.
文摘This paper proposes a hybrid short-term load forecasting method,which is based on the fuzzy combination weights as well as the empirical mode decomposition process(FCW-EMD),and support vector machine optimized via the Bat algorithm as well as the Kalman filtering process(KF-BA-SVM).The subjective weight is presented as a new theory and is applied to capture the inherent correlation effectively among hourly loads.Based on the proposed objective weights and subjective weights,the fuzzy combination weights theory(FCW)-a new similar day selection theory is presented,which improves the accuracy of the similar day selection,and correspondingly,makes the original data for EMD processing decrease dramatically.BA is introduced to optimize parameters of the SVM model for further improving the forecasting accuracy.Using the decomposed load series via empirical model decomposition(EMD)as inputs to SVM and further correcting the output of SVM via KF,a hybrid FCW-EMD and KF-BA-SVM short-term load forecasting method is established.Numerical case studies on the load forecasting of a transformer substation in south China show that the proposed hybrid forecasting model outperforms other forecasting methods and effectively improves the prediction accuracy.