Publications

Vehicular fuel consumption and CO2 emission estimation model integrating novel driving behavior data using machine learning

Published in Energies, 2024

This paper introduces a method for monthly vehicular fuel consumption and CO2 emission estimation using random forest (RF) regression. The method employs driving behavior data, specifically dangerous driving behavior.

Recommended citation: Wang Z, Mae M, Nishimura S, Matsuhashi R. Vehicular fuel consumption and CO2 emission estimation model integrating novel driving behavior data using machine learning. Energies. https://doi.org/10.3390/en17061410 http://ziyangwangacademics.github.io/files/paper5.pdf

Estimating vehicular fuel consumption and CO2 emissions by machine learning using only speed and acceleration

Published in Journal of Japan Society of Energy and Resources, 2023

This paper introduces a method for instantaneous vehicular fuel consumption assessment using random forest (RF) regression. The method employs driving data, specifically speed and acceleration.

Recommended citation: Maroju R, Nishimura S, Wang Z, Matsuhashi R. Estimating Vehicular Fuel Consumption and CO2 Emissions by Machine Learning Using Only Speed and Acceleration. Journal of Japan Society 2023. https://doi.org/10.24778/jjser.44.1_30 http://ziyangwangacademics.github.io/files/paper4.pdf

Intrusive and non-intrusive early warning systems for thermal discomfort by analysis of body surface temperature

Published in Applied Energy, 2023

This paper delves further into the concept of Relative Thermal Sensation (RTS) and explores both its intrusive and non-intrusive assessment methods. The preliminary work on this topic can be found in our earlier paper titled “Proposal of relative thermal sensation: Another dimension of thermal comfort and its investigation.”

Recommended citation: Wang Z, Matsuhashi R, Onodera H. Intrusive and non-intrusive early warning systems for thermal discomfort by analysis of body surface temperature. Appl Energy 2023;329:120283. https://doi.org/10.1016/j.apenergy.2022.120283. http://ziyangwangacademics.github.io/files/AppliedEnergy1.pdf

Towards wearable thermal comfort assessment framework by analysis of heart rate variability

Published in Building and Environment, 2022

This paper introduces a real-time thermal comfort assessment method based on the analysis of heart rate variablity (HRV). The heartbeat data were measured using a portable, non-intrusive, low-cost wearable heartbeat sensor.

Recommended citation: Wang Z, Matsuhashi R, Onodera H. Towards wearable thermal comfort assessment framework by analysis of heart rate variability. Build Environ 2022:109504. https://doi.org/10.1016/j.buildenv.2022.109504. http://ziyangwangacademics.github.io/files/BuildingandEnvironment1.pdf

Proposal of relative thermal sensation: Another dimension of thermal comfort and its investigation

Published in IEEE Access, 2021

This paper introduces the concept of Relative Thermal Sensation (RTS) and presents a preliminary investigation of its assessment method using an intrusive approach. Further discussions on this topic can be found in our subsequent paper titled “Intrusive and non-intrusive early warning systems for thermal discomfort by analysis of body surface temperature.”

Recommended citation: Wang Z, Onodera H, Matsuhashi R. Proposal of relative thermal sensation: Another dimension of thermal comfort and its investigation. IEEE Access 2021;9:36266–81. https://doi.org/10.1109/ACCESS.2021.3062393. http://ziyangwangacademics.github.io/files/IEEEAccess1.pdf

Ziyang Wang