Group Daily Arrival Prediction Based on A Hybrid Model Combing Autoregressive Integrated Moving Average Model and Back Propagation Neural Network
- Resource Type
- Conference
- Authors
- Zhu, Xiaoling; Zhang, Xi; Shi, Ge; Wang, Yashen
- Source
- 2020 3rd International Conference on Unmanned Systems (ICUS) Unmanned Systems (ICUS), 2020 3rd International Conference on. :227-232 Nov, 2020
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Computing and Processing
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
Predictive models
Neurons
Data models
Analytical models
Urban areas
Solid modeling
Backpropagation
Group Daily Arrival Prediction
Hybrid Model
Autoregressive Integrated Moving Average Model
Back Propagation Neural Network
- Language
To solve the problem of predicting daily arrival number of people belonging to a specific group, this paper proposes a hybrid model which integrates linear component (from ARIMA model) with non-linear component (from BP neural network). The experimental results indicate that, hybrid methodology that has both linear and nonlinear modeling capabilities is a good strategy for practical use.