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References from A deep neural network based model for the prediction of hybrid electric vehicles carbon dioxide emissions. Local targets link to admitted publications; unresolved targets remain external evidence.
Study of the effect of contraction of cross-sectional area on flow energy merger in hybrid pneumatic power system
10.1016/j.apenergy.2009.03.002 · 2009 · External reference
A comprehensive study of key electric vehicle (EV) components, technologies, challenges, impacts, and future direction of development
10.3390/en10081217 · 2017 · External reference
Fully electric and plug-in hybrid cars - an analysis of learning rates, user costs, and costs for mitigating CO 2 and air pollutant emissions
10.1016/j.jclepro.2018.12.019 · 2019 · External reference
Hybrid electric vehicles and their challenges: a review
10.1016/j.rser.2013.08.097 · 2014 · External reference
An overview of fuel cell technology: fundamentals and applications
10.1016/j.rser.2014.01.012 · 2014 · External reference
Layout design and energetic analysis of a complex diesel parallel hybrid electric vehicle
10.1016/j.apenergy.2014.08.007 · 2014 · External reference
Comparing parallel hybrid electric vehicle powertrains for real-world driving
2019 · External reference
Emissions impacts and benefits of plug-in hybrid electric vehicles and vehicle-to-grid services
10.1021/es802324j · 2009 · External reference
A comprehensive overview of hybrid electric vehicle: Powertrain configurations, powertrain control techniques and electronic control units
10.1016/j.enconman.2010.09.028 · 2011 · External reference
Overview of different hybrid vehicle architectures
10.1016/j.ifacol.2018.07.036 · 2018 · External reference
Comparative study of real-time HEV energy management strategies
10.1109/tvt.2017.2727069 · 2017 · External reference
Energy management strategies of connected HEVs and PHEVs: recent progress and outlook
10.1016/j.pecs.2019.04.002 · 2019 · External reference
Power management strategy for a parallel hybrid electric truck
10.1109/tcst.2003.815606 · 2003 · External reference
Robust coordinated control for hybrid electric bus with single-shaft parallel hybrid powertrain
10.1049/iet-cta.2014.0321 · 2015 · External reference
Control strategies for parallel hybrid electric vehicles
10.1016/s1474-6670(17)30392-0 · 2004 · External reference
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Machine learning: a review of classification and combining techniques
10.1007/s10462-007-9052-3 · 2006 · External reference
Distributed dynamic programming
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Classification of Alzheimer's disease and Parkinson's disease by using machine learning and neural network methods
2010 · External reference
Overview of neural networks
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Rule extraction algorithm for deep neural networks: a review
2016 · External reference
Deep-learning: Investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data
10.1186/s13321-017-0226-y · 2017 · External reference
Comparison of deep learning with multiple machine learning methods and metrics using diverse drug discovery data sets
10.1021/acs.molpharmaceut.7b00578 · 2017 · External reference
Overview of modern design of experiments methods for computational simulations
2003 · External reference
Calculation of mass emissions, oxygen mass fraction and thermal capacity of the inducted charge in SI and diesel engines from exhaust and intake gas analysis
10.1016/j.fuel.2010.08.025 · 2011 · External reference
Cost-optimized design of a dual-mode diesel parallel hybrid electric vehicle for several driving missions and market scenarios
10.1016/j.apenergy.2016.05.080 · 2016 · External reference
Sampling based on sobol′ sequences for monte carlo techniques applied to building simulations
2011 · External reference
Computational investigations of low-discrepancy sequences
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History and development of dynamic programming
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Investigating the impact of data normalization on classification performance
10.1016/j.asoc.2019.105524 · 2020 · External reference
Impact of data normalization on stock index forecasting
2014 · External reference
Normalization and integration of large-scale metabolomics data using support vector regression
10.1007/s11306-016-1026-5 · 2016 · External reference
Unresolved reference
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The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
10.1186/s12864-019-6413-7 · 2020 · External reference
Correlation and the coefficient of determination
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An R-squared measure of goodness of fit for some common nonlinear regression models
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