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Statistical methods versus neural networks in transportation research: Differences, similarities and some insights

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References

1996Combining kohonen maps with arima time series models to forecast traffic flow851 cited
2002Dynamic Bus Arrival Time Prediction with Artificial Neural Networks367 cited
2002Combining neural network model with seasonal time series ARIMA model345 cited
2003Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks211 cited
2008Neural network based temporal feature models for short-term railway passenger demand forecasting211 cited
2000A comparison of the predictive potential of artificial neural networks and nested logit models for commuter mode choice182 cited
1995Automated detection of lane-blocking freeway incidents using artificial neural networks150 cited
2001A Study of Hybrid Neural Network Approaches and the Effects of Missing Data on Traffic Forecasting149 cited
2005Multilayer feedforward networks for transportation mode choice analysis: An analysis and a comparison with random utility models135 cited
1997Evaluating public transport efficiency with neural network models133 cited
2008Travel Mode Choice Modeling with Support Vector Machines127 cited
2006Application of radial basis function and generalized regression neural networks in non-linear utility function specification for travel mode choice modelling126 cited
2000Trip distribution forecasting with multilayer perceptron neural networks: A critical evaluation120 cited

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2006An integrated transportation decision support system for transportation policy decisions: The case of Turkey86 cited

2005Prediction Model of Bus Arrival Time for Real-Time Applications86 cited

2007Modelling drivers' compliance and route choice behaviour in response to travel information84 cited

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2020Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models468 cited
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