KEY-COST DRIVERS SELECTION IN LOCAL PUBLIC BUS TRANSPORT SERVICES THROUGH MACHINE LEARNING

被引：7

作者：

Avenali, Alessandro ^{[1
]}

Catalano, Giuseppe ^{[1
]}

D'Alfons, Tiziana ^{[1
]}

Matteucci, Giorgio ^{[1
]}

Manno, Andrea ^{[2
]}

机构：

[1] Sapienza Univ Roma, Dept Comp Control & Management Engn, Rome, Italy

[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, Milan, Italy

来源：

URBAN TRANSPORT XXIII | 2018年 / 176卷

关键词：

standard costs; local public transport; fiscal federalism; cost drivers; machine learning; TRANSIT SYSTEMS; EFFICIENCY;

D O I：

10.2495/UT170141

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This paper is aimed at developing a workable model for the identification of key-cost drivers in the Italian Local Public Bus Transport (LPBT) sector. Disaggregated information about costs, technical characteristics and environmental characteristics have been collected by means of questionnaires sent to LPBT companies producing more than 500 million bus revenue kilometres in Italy in 2011. A supervised regression model is built by training a regularized Artificial Neural Network in order to determine the quantitative and qualitative characteristics that contribute to explaining the variability of the driving personnel and the unit cost of the fleet (which usually covers more than 50% of the total economic cost) and the remaining portion of the unit cost. The proposed models could be an effective and simple tool for local authorities to validate reserve prices in tender procedures.

引用

页码：155 / 166

页数：12

共 11 条

[1] Predicting costs of local public bus transport services through machine learning methods
Amicosante, Andrea
Avenali, Alessandro
D'Alfonso, Tiziana
Giagnorio, Mirko
Manno, Andrea
Matteucci, Giorgio
EXPERT SYSTEMS WITH APPLICATIONS, 2025, 260
[2] Rail versus bus local public transport services: A social cost comparison methodology
Avenali, Alessandro
Catalano, Giuseppe
Gregori, Martina
Matteucci, Giorgio
TRANSPORTATION RESEARCH INTERDISCIPLINARY PERSPECTIVES, 2020, 7
[3] Exploring the Application of Machine Learning Algorithms to the City Public Bus Transport
Alicea, Michael
McDonald, Arlen P.
Tang, Chunyang
Yang, Jeong
2020 IEEE 14TH INTERNATIONAL CONFERENCE ON BIG DATA SCIENCE AND ENGINEERING (BIGDATASE 2020), 2020, : 22 - 27
[4] Assessing standard costs in local public bus transport: A hybrid cost model
Avenali, Alessandro
Boitani, Andrea
Catalano, Giuseppe
D'Alfonso, Tiziana
Matteucci, Giorgio
TRANSPORT POLICY, 2018, 62 : 48 - 57
[5] Driving behaviors analysis for public transport drivers in Kuwait: a machine learning approach to drivers safety
Sharaf AlKheder
Hanaa Al-Saleh
Neural Computing and Applications, 2025, 37 (7) : 5289 - 5307
[6] Cost structure and technological change of local public transport: the Kaohsiung City Bus case
Chiang, JSEW
Chen, YW
APPLIED ECONOMICS, 2005, 37 (12) : 1399 - 1410
[7] Classification of Services through Feature Selection and Machine Learning in 5G Networks
Automatic Control and Computer Sciences, 2023, 57 : 589 - 599
[8] Classification of Services through Feature Selection and Machine Learning in 5G Networks
Rajak, Anjali
Tripathi, Rakesh
AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2023, 57 (06) : 589 - 599
[9] Key wastes selection and prediction improvement for biogas production through hybrid machine learning methods
Chiu, Ming-Chuan
Wen, Chih-Yuan
Hsu, Hsin-Wei
Wang, Wei-Cheng
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 52
[10] Identification and Analysis of a Unique Cell Selection Phenomenon in Public Unlicensed Cellular Networks Through Machine Learning
Kala, Srikant Manas
Sathya, Vanlin
Dahiya, Kunal
Higashino, Teruo
Yamaguchi, Hirozumi
IEEE ACCESS, 2022, 10 : 87282 - 87301

← 1 2 →