Comparison of two approaches for modeling freight movement at seaports

Journal of Computing in Civil Engineering

Volumn 15, Issue 4, 2001, Pages 284-291

  Al Deek, Haitham M ^a,b  

^a ASCE ^*  (United States)

^b University of Central Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION NEURAL NETWORKS; FREIGHT TRAFFIC; SEAPORT;

COMPUTER SIMULATION; DATABASE SYSTEMS; NEURAL NETWORKS; PLANNING; REGRESSION ANALYSIS;

FREIGHT TRANSPORTATION;

EID: 0035482282     PISSN: 08873801     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)0887-3801(2001)15:4(284)     Document Type: Article

References (15)

1. Truck trip generation models for seaports with container/trailer operation
2. Model for heavy truck freight movement on external road network connecting with Florida ports, phase I
3. Truck trip generation characteristics of nonresidential land uses
4. Freight movement study
5. Comparison between neural networks and multiple regression approaches for developing freight trip generation and modal split models with specific applications to Florida's deep seaports
6. Evaluation of artificial neural network applications in transportation engineering
7. Behavioral mode choice model comparing air and truck freight transport
8. Theoretical development and preliminary testing of mathematical model for predicting freight modal split
9. Performance of automatic ANN-based incident detection on freeways
10. Study on estimation and aggregation of disaggregate models of mode choice for freight transport
11. Estimating truck travel patterns in urban areas