Wavelet neural network prediction algorithm based on improved implicit generalized predictive control

2018 ◽  
Author(s):  
Wu Qiang ◽  
Zhou Ying ◽  
Li Muwei
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Wavelet Neural Network ◽  
Prediction Algorithm ◽  
Generalized Predictive Control ◽  
Neural Network Prediction ◽  
Network Prediction

scholarly journals Research on bus elastic departure interval based on Wavelet Neural Network

2021 ◽  
Vol 261 ◽  
pp. 03052
Author(s):  
Zhe Lv ◽  
Jiayu Zou ◽  
Zhongyu Zhao
Keyword(s):  
Neural Network ◽  
Prediction Method ◽  
Wavelet Neural Network ◽  
Economic Costs ◽  
Passenger Flow ◽  
Flow Prediction ◽  
Intelligent Optimization Algorithm ◽  
Neural Network Prediction ◽  
Network Prediction ◽  
Important Basis

In recent years, more and more people choose to travel by bus to save time and economic costs, but the problem of inaccurate bus arrival has become increasingly prominent. The reason is the lack of scientific planning of departure time. This paper takes the passenger flow as an important basis for departure interval, proposes a passenger flow prediction method based on wavelet neural network, and uses intelligent optimization algorithm to study the bus elastic departure interval. In this paper, the wavelet neural network prediction model and the elastic departure interval optimization model are established, and then the model is solved by substituting the data, and finally the theoretical optimal departure interval is obtained.

The Study of Prediction Model Based on Morlet Wavelet Neural Network

2011 ◽  
Vol 121-126 ◽  
pp. 4847-4851 ◽  
Author(s):  
Hui Zhen Yang ◽  
Wen Guang Zhao ◽  
Wei Chen ◽  
Xu Quan Chen
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Network Model ◽  
Neural Network Model ◽  
Learning Algorithm ◽  
Morlet Wavelet ◽  
Wavelet Neural Network ◽  
Model Based ◽  
Neural Network Prediction ◽  
Network Prediction

Wavelet Neural Network (WNN) is a new form of neural network combined with the wavelet theory and artificial neural network. The wavelet neural network model based on Morlet wavelet and the corresponding learning algorithm were studied in this paper. And through learning the wavelet neural network model is applied to all kinds of engineering examples, it proved that the wavelet neural network prediction model which has a more flexible and efficient function approximation ability and strong fault tolerance, and with high predicting precision.

Physical and chemical indexes of synthetic base oils based on a wavelet neural network and genetic algorithm

2019 ◽  
Vol 72 (1) ◽  
pp. 116-121 ◽  
Author(s):  
Guomin Wang ◽  
Yuanyuan Wu ◽  
Haifu Jiang ◽  
Yanjie Zhang ◽  
Jiarong Quan ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Empirical Formula ◽  
Viscosity Index ◽  
Wavelet Neural Network ◽  
Lubricating Oil ◽  
Content Type ◽  
Neural Network Prediction ◽  
Network Prediction ◽  
Physical And Chemical

Purpose The purpose of this paper is to use the wavelet neural network and genetic algorithm to study the effects of polyalphaolefin, TMP108 and OCP0016 on the kinematic viscosity, viscosity index and pour point of lubricating oil. Design/methodology/approach Wavelet neural network is used to train the known samples, test the unknown samples and compare the obtained results with those obtained with a traditional empirical formula. Findings It is found that the wavelet neural network prediction value is closer to the experimental value than the traditional empirical formula calculation value. Originality/value The results show that the wavelet neural network can be used to study the physical and chemical indexes of lubricating oil.

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