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A Novel Interaction Protocol of a Multiagent System for the Study of Alternative Decisions Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Determining the Criteria for Setting Input Parameters of the Fuzzy Inference Model of P&R Car Parks Locating

Authors : Michał Lower, Anna Lower

Published in: Computational Collective Intelligence

Publisher: Springer International Publishing

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Abstract

The paper presents the fuzzy inference model of evaluation of P&R facilities location. In such a system there are car parks where travellers can change from car to public transport. Recognising proper locations of the P&R facilities is a key aspect for the system. On the basis of previous studies it was found that developing algorithms supporting the determination of input parameters to the model is necessary. The authors created recurrent algorithm for determining the parameter of the road quality. For the parameters of quantity of public transport means and the distance to the city centre the algorithm based on the exponential function was made. For determining the parameter describing the connection to the main road the fuzzy inference model was built. Thanks to the developed methodology the model of P&R locating has become more universal and possible to use for a broader group of experts.

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Metadata
Title
Determining the Criteria for Setting Input Parameters of the Fuzzy Inference Model of P&R Car Parks Locating
Authors
Michał Lower
Anna Lower
Copyright Year
2016
Book
Computational Collective Intelligence

Print ISBN: 978-3-319-45242-5

Electronic ISBN: 978-3-319-45243-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-45243-2_22

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