Tongna Liu

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This paper put forward a new method of the fuzzy rules and wavelet neural network model for mid-long term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of fuzzy rules. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast(More)
This paper proposes a new method for mid-long term load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno Fuzzy Logic System, and establishing the fuzzy model for load forecasting. lt can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the mid-long term electric load(More)
This paper proposes a new method for load forecasting—fuzzy rules by genetic algorithms based on Takagi-Sugeno Fuzzy Logic System, and establishing the fuzzy model for load forecasting. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the daily electric load forecasting.
This paper proposes a new method for load forecasting—fuzzy rules by genetic algorithms based on Takagi-Sugeno Fuzzy Logic System, and establishing the fuzzy model for load forecasting. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the short-term electric load forecasting.
Standard Hidden Markov Models (HMMs) approaches used for condition assessment of bearings assume that all the possible system states are fixed and known a priori and that training data from all of the associated states are available. Moreover, the training procedure is performed offline, and only once at the beginning, with the available training set. These(More)
This paper put forward a new method of the wavelet neural network model for mid-long term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of ANN. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the(More)
  • Tongna Liu
  • 2009 Third International Symposium on Intelligent…
  • 2009
This paper proposes a new method for load forecasting— the wavelet neural network model for load forecasting. The neural call function is basis of nonlinear wavelets. A wavelet network is composed by the wavelet basis function. The global optimum solution is got. We overcome the intrinsic defects of a artificial neural network that its learning(More)
This paper put forward a new method of the SVM and wavelet neural network model for short-term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of SVM. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested(More)
The principle and step of performance evaluation of project management based on SVM and fuzzy rules are studied. The index system of performance evaluation of project management is set up. Then we built up the evaluation model on SVM and fuzzy rules. Finally, take some samples of project for an example, we carry on this model to instance. It can take a(More)