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Daily activity pattern recognition by using support vector machines with multiple classes · Study

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ArticleDaily activity pattern recognition by using support vector machines with multiple classes

Mahdieh Allahviranloo2013

Article2013

Daily activity pattern recognition by using support vector machines with multiple classes

Mahdieh Allahviranloo · Will W. Recker

95 citations·0/0 files stored·Transportation Research Part B Methodological

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Human Mobility and Location-Based Analysis Transportation Planning and Optimization Context-Aware Activity Recognition Systems

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 95 citations exist upstream.

References

2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code 1979Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code 2007Learning and inferring transportation routines 2001Activity-based disaggregate travel demand model system with activity schedules 2003A learning-based transportation oriented simulation system 2004A multiple discrete–continuous extreme value model: formulation and application to discretionary time-use decisions 2004Comprehensive Econometric Microsimulator for Daily Activity-Travel Patterns 2000ALBATROSS : a learning based transportation oriented simulation system

Cited by

2017A time-use activity-pattern recognition model for activity-based travel demand modeling 2020Discovering latent activity patterns from transit smart card data: A spatiotemporal topic model 2019Detecting Travel Modes Using Rule-Based Classification System and Gaussian Process Classifier 2019A Dynamic Discrete Choice Activity-Based Travel Demand Model 2017Travel mode estimation for multi-modal journey planner 2024Comparing hundreds of machine learning and discrete choice models for travel demand modeling: An empirical benchmark 2017Reconstructing Activity Location Sequences From Incomplete Check-In Data: A Semi-Markov Continuous-Time Bayesian Network Model 2014A multi-day activity-based inventory routing model with space–time–needs constraints

Details

Year2013

Typearticle

Published2013-10-17

VenueTransportation Research Part B Methodological

ISSN-L0191-2615

Languageen

Citations95

Files0 public / 0

ShelfHuman Mobility and Location-Based Analysis

Identifiers

doi10.1016/j.trb.2013.09.008

openalex_workW2064980505

Links

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