Application in Dynamic Path Selection for Emergency Vehicles Based on Hybrid Cuckoo Algorithm Optimizing Neural Network Model

2018 ◽  
Vol 16 (6) ◽  
Author(s):  
Feng Yang ◽  
Chunming Ye ◽  
Jianfeng Ren
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Path Selection ◽  
Emergency Vehicles ◽  
Dynamic Path ◽  
Selection For ◽  
Cuckoo Algorithm

A Novel Quantum Neural Network Model with Variable Selection for Short Term Load Forecasting

2010 ◽  
Vol 20-23 ◽  
pp. 612-617 ◽  
Author(s):  
Wei Sun ◽  
Yu Jun He ◽  
Ming Meng
Keyword(s):  
Neural Network ◽  
Variable Selection ◽  
Network Model ◽  
Neural Network Model ◽  
Load Forecasting ◽  
Short Term ◽  
Bp Network ◽  
Quantum Neural Network ◽  
Short Term Load Forecasting ◽  
Selection For

The paper presents a novel quantum neural network (QNN) model with variable selection for short term load forecasting. In the proposed QNN model, first, the combiniation of maximum conditonal entropy theory and principal component analysis method is used to select main influential factors with maximum correlation degree to power load index, thus getting effective input variables set. Then the quantum neural network forecating model is constructed. The proposed QNN forecastig model is tested for certain province load data. The experiments and the performance with QNN neural network model are given, and the results showed the method could provide a satisfactory improvement of the forecasting accuracy compared with traditional BP network model.

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