Related references
Note: Only part of the references are listed.Vehicle Trajectory Interpolation Based on Ensemble Transfer Regression
Jianhua Xiao et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2022)
EdgeLSTM: Towards Deep and Sequential Edge Computing for IoT Applications
Di Wu et al.
IEEE-ACM TRANSACTIONS ON NETWORKING (2021)
Cost Analysis of Driverless Truck Operations
Albin Engholm et al.
TRANSPORTATION RESEARCH RECORD (2020)
Modelling and evaluation of a biomethane truck for transport performance and cost
Anil K. Madhusudhanan et al.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT (2020)
A Parallel Genetic Algorithm Framework for Transportation Planning and Logistics Management
Dmitri I. Arkhipov et al.
IEEE ACCESS (2020)
Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
Oskar Wysocki et al.
ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2019, PT I (2019)
Neural Models for Benchmarking of Truck Driver Fuel Economy Performance
Alwyn J. Hoffman
IJCCI: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL INTELLIGENCE (2019)
Fine-Grained Fuel Consumption Prediction
Chenguang Fang et al.
PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM '19) (2019)
Generative Adversarial Networks An overview
Antonia Creswell et al.
IEEE SIGNAL PROCESSING MAGAZINE (2018)
Fuel consumption model for heavy duty diesel trucks: Model development and testing
Jinghui Wang et al.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT (2017)
Database Meets Deep Learning
Wei Wang et al.
SIGMOD RECORD (2016)
Prediction of fuel consumption of mining dump trucks: A neural networks approach
Elnaz Siami-Irdemoosa et al.
APPLIED ENERGY (2015)
Fuel-Optimal Cruising Strategy for Road Vehicles With Step-Gear Mechanical Transmission
Shaobing Xu et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2015)
Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time
Behrang Asadi et al.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2011)
Artificial Neural Network and stepwise multiple range regression methods for prediction of tractor fuel consumption
Fatemeh Rahimi-Ajdadi et al.
MEASUREMENT (2011)
Virginia Tech Comprehensive Power-Based Fuel Consumption Model: Model development and testing
Hesham A. Rakha et al.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT (2011)
Development of VT-Micro model for estimating hot stabilized light duty vehicle and truck emissions
H Rakha et al.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT (2004)
A perspective view and survey of meta-learning
R Vilalta et al.
ARTIFICIAL INTELLIGENCE REVIEW (2002)