Predicting and improving smart mobility: a robust model-based approach to the BikeMi BSS = Prevedere e migliorare la mobilita smart: un approccio robusto di classificazione applicato a BikeMi

Andrea Cappozzo; F. Greselin; G. Manzi

Predicting and improving smart mobility: a robust model-based approach to the BikeMi BSS = Prevedere e migliorare la mobilita smart: un approccio robusto di classificazione applicato a BikeMi

Andrea Cappozzo
, F. Greselin
, G. Manzi

Risultato della ricerca: Contributo in libro › Contributo a conferenza

Abstract

[Ita:]I sistemi di Bike Sharing giocano un ruolo centrale nella mobilita sosteni- ` bile, uno dei sei pilastri che indentificano una Smart City. Motivati da un set di dati disponibile online, questo lavoro presenta l’utilizzo di due modelli di classificazione robusta per prevedere il manifestarsi di situazioni in cui una bike station sia piena e/o vuota, cos`ı creando perdita di domanda ed insoddisfazione nei clienti. Esperimenti di classificazione sulle stazioni BikeMi nel centro di Milano evidenziano l’efficacia dei metodi proposti.

Lingua originale	Inglese
Titolo della pubblicazione ospite	Smart Statistics for Smart Applications
Pagine	737-742
Numero di pagine	6
Stato di pubblicazione	Pubblicato - 2019
Evento	Smart Statistics for Smart Applications - Milano Durata: 18 giu 2019 → 21 giu 2019

Convegno

Convegno	Smart Statistics for Smart Applications
Città	Milano
Periodo	18/6/19 → 21/6/19

OSS delle Nazioni Unite

Questo processo contribuisce al raggiungimento dei seguenti obiettivi di sviluppo sostenibile

SDG 11 Città e comunità sostenibili

Keywords

Bike Sharing System
Robust Classification
Impartial Trimming
Smart Mobility

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title = "Predicting and improving smart mobility: a robust model-based approach to the BikeMi BSS = Prevedere e migliorare la mobilita smart: un approccio robusto di classificazione applicato a BikeMi",

abstract = "Bike Sharing Systems play a central role in what is identified to be one of the six pillars of a Smart City: smart mobility. Motivated by a freely available dataset, we discuss the employment of two robust model-based classifiers for pre- dicting the occurrence of situations in which a bike station is either empty or full, thus possibly creating demand loss and customer dissatisfaction. Experiments on BikeMi stations located in the central area of Milan are provided to underline the benefits of the proposed methods.",

keywords = "Bike Sharing System, Robust Classification, Impartial Trimming, Smart Mobility, Bike Sharing System, Robust Classification, Impartial Trimming, Smart Mobility",

author = "Andrea Cappozzo and F. Greselin and G. Manzi",

year = "2019",

language = "English",

isbn = "9788891915108",

pages = "737--742",

booktitle = "Smart Statistics for Smart Applications",

note = "Smart Statistics for Smart Applications ; Conference date: 18-06-2019 Through 21-06-2019",

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AU - Cappozzo, Andrea

AU - Greselin, F.

AU - Manzi, G.

PY - 2019

Y1 - 2019

N2 - Bike Sharing Systems play a central role in what is identified to be one of the six pillars of a Smart City: smart mobility. Motivated by a freely available dataset, we discuss the employment of two robust model-based classifiers for pre- dicting the occurrence of situations in which a bike station is either empty or full, thus possibly creating demand loss and customer dissatisfaction. Experiments on BikeMi stations located in the central area of Milan are provided to underline the benefits of the proposed methods.

AB - Bike Sharing Systems play a central role in what is identified to be one of the six pillars of a Smart City: smart mobility. Motivated by a freely available dataset, we discuss the employment of two robust model-based classifiers for pre- dicting the occurrence of situations in which a bike station is either empty or full, thus possibly creating demand loss and customer dissatisfaction. Experiments on BikeMi stations located in the central area of Milan are provided to underline the benefits of the proposed methods.

KW - Bike Sharing System

KW - Robust Classification

KW - Impartial Trimming

KW - Smart Mobility

KW - Bike Sharing System

KW - Robust Classification

KW - Impartial Trimming

KW - Smart Mobility

UR - http://hdl.handle.net/10807/306443

UR - https://it.pearson.com/docenti/universita/partnership/sis.html

M3 - Conference contribution

SN - 9788891915108

SP - 737

EP - 742

BT - Smart Statistics for Smart Applications

T2 - Smart Statistics for Smart Applications

Y2 - 18 June 2019 through 21 June 2019

ER -

Predicting and improving smart mobility: a robust model-based approach to the BikeMi BSS = Prevedere e migliorare la mobilita smart: un approccio robusto di classificazione applicato a BikeMi

Abstract

Convegno

OSS delle Nazioni Unite

Keywords

Altri file e collegamenti

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