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EBookClubs

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Book Investigation of a Neural Network Model for Freeway Incident Detection

Download or read book Investigation of a Neural Network Model for Freeway Incident Detection written by B. Bavarian and published by . This book was released on 1991 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book An Application of Artificial Neural Networks in Freeway Incident Detection

Download or read book An Application of Artificial Neural Networks in Freeway Incident Detection written by Sujeeva A. Weerasuriya and published by . This book was released on 1998 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: A modified form of a conventional detection rate was introduced to capture full capability of AIDMs in detecting incident patterns in the freeway traffic flow. Results of this study suggest that double hidden layer networks are better than single hidden layer networks. The study has demonstrated the potential of ANNs to improve the reliability using double layer networks when freeway geometric information is included in the model.

Book Evaluation of Adaptive Neural Network Models for Freeway Incident Detection

Download or read book Evaluation of Adaptive Neural Network Models for Freeway Incident Detection written by Dipti Srinivasan and published by . This book was released on 2018 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated incident detection is an essential component of a modern freeway traffic monitoring system. A number of neural network-based incident detection models have been tested independently over the past decade. This paper evaluates the adaptability of three promising neural network models for this problem: multi-layer feed-forward neural network (MLF), basic probabilistic neural network (BPNN) and constructive probabilistic neural network (CPNN). These three models have been developed on an original freeway site in Singapore and then adapted to a new freeway site in California. Apart from their incident detection performances, their adaptation strategies and network sizes have also been compared. Results of this study show that the MLF model has the best incident detection performance at the development site while CPNN model has the best performance after model adaptation at the new site. In addition, the adaptation method for CPNN model is relatively more automatic. The efficient network pruning procedure for the CPNN network resulted in a smaller network size, making it easier to implement it for real-time application. The results suggest that CPNN model has the highest potential for use in an operational automatic incident detection system for freeways.

Book Freeway Incident Detection Using Artificial Neural Networks

Download or read book Freeway Incident Detection Using Artificial Neural Networks written by Killion Bruce Roh and published by . This book was released on 1996 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Neural Network Model for Automatic Traffic Incident Detection

Download or read book Neural Network Model for Automatic Traffic Incident Detection written by Hojjat Adeli and published by . This book was released on 2001 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. In this research, a multi-paradigm intelligent system approach and several innovative algorithms were developed for solution of the freeway traffic incident detection problem employing advanced signal processing, pattern recognition, and classification techniques. The methodology effectively integrates fuzzy, wavelet, and neural computing techniques to improve reliability and robustness.

Book Wavelet neural Network Models for Automatic Freeway Incident Detection

Download or read book Wavelet neural Network Models for Automatic Freeway Incident Detection written by Asim Salimul Karim and published by . This book was released on 2001 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Neural Networks in Transport Applications

Download or read book Neural Networks in Transport Applications written by Veli Himanen and published by Routledge. This book was released on 2019-07-09 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: First published in 1998, this volume enters the debate on human behaviour in the form of neural networks in a spatial context. As most transportation research techniques had been developed in the 1960s and 1970s, these authors sought to bring that research into the modern era. Featuring 17 articles from 37 contributors, it begins with an overview and proceeds to examine aspects of travel behaviour, traffic flow and traffic management.

Book Adaptive Neural Network Models for Automatic Incident Detection on Freeways

Download or read book Adaptive Neural Network Models for Automatic Incident Detection on Freeways written by Dipti Srinivasan and published by . This book was released on 2005 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated incident detection (AID) is an essential component of an Advanced Traffic Management and Information Systems (ATMIS), which provides round the clock incident detection, and helps initiate the required action in case of an accident or incident. This paper evaluates three promising neural network models: multi-layer feed-forward neural network (MLF), basic probabilistic neural network (BPNN) and constructive probabilistic neural network (CPNN) for their incident detection performance. An important consideration in neural network-based incident detection systems is the deployment of a trained neural network on traffic systems with considerably different driving conditions. The models were developed and tested on an original freeway site in Singapore, and tested on a new freeway site in the US for their adaptability. The paper presents comparative evaluation in terms of their classification accuracy, adaptability, and network size. Results indicate that although the MLF model gives excellent classification results on the development site, the CPNN model outperforms the other two in terms of its adaptability and flexible structure. The results suggest that CPNN model has the highest potential for use in an operational automatic incident detection system for freeways.