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A platform for research: civil engineering, architecture and urbanism
Neural Network-Based Combined Synthetic Model of Trip Generation and Distribution
Some direct synthetic models for trip generation, distribution and model choice have been previously proposed in order to substitute the traditional four-step sequential travel demand model. However, the previous model based approach has limitations in real world applications where we have to deal with a large number of zones and various parameters effecting travel demand.
In this study, we propose a neural network-based combined model for trip generation, distribution and modal spilt. The experimental results showed that the proposed direct demand model using the neural network model is an attractive proposition, particularly in areas where we have to deal with a large number of zones to determine future trips.
Neural Network-Based Combined Synthetic Model of Trip Generation and Distribution
Some direct synthetic models for trip generation, distribution and model choice have been previously proposed in order to substitute the traditional four-step sequential travel demand model. However, the previous model based approach has limitations in real world applications where we have to deal with a large number of zones and various parameters effecting travel demand.
In this study, we propose a neural network-based combined model for trip generation, distribution and modal spilt. The experimental results showed that the proposed direct demand model using the neural network model is an attractive proposition, particularly in areas where we have to deal with a large number of zones to determine future trips.
Neural Network-Based Combined Synthetic Model of Trip Generation and Distribution
Kim, Daehyon (author) / Chang, Yohan (author) / Yang, Kyong-Uk (author)
International Journal of Urban Sciences ; 12 ; 18-27
2008-06-01
10 pages
Article (Journal)
Electronic Resource
Unknown
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