A review of artificial intelligence based building energy use prediction: Contrasting the capabilities of single and ensemble prediction models
Z Wang, RS Srinivasan - Renewable and Sustainable Energy Reviews, 2017 - Elsevier
Building energy use prediction plays an important role in building energy management and
conservation as it can help us to evaluate building energy efficiency, conduct building …
conservation as it can help us to evaluate building energy efficiency, conduct building …
Road traffic forecasting: Recent advances and new challenges
Due to its paramount relevance in transport planning and logistics, road traffic forecasting
has been a subject of active research within the engineering community for more than 40 …
has been a subject of active research within the engineering community for more than 40 …
[HTML][HTML] IntelliHealth: a medical decision support application using a novel weighted multi-layer classifier ensemble framework
Accuracy plays a vital role in the medical field as it concerns with the life of an individual.
Extensive research has been conducted on disease classification and prediction using …
Extensive research has been conducted on disease classification and prediction using …
HMV: A medical decision support framework using multi-layer classifiers for disease prediction
Decision support is a crucial function for decision makers in many industries. Typically,
Decision Support Systems (DSS) help decision-makers to gather and interpret information …
Decision Support Systems (DSS) help decision-makers to gather and interpret information …
Constructing cooperative intelligent transport systems for travel time prediction with deep learning approaches
Drivers and traffic system planners require accurate forecasting of future travel times. To
alleviate traffic congestion on Taiwan's Provincial Highway No. 61, this study considers …
alleviate traffic congestion on Taiwan's Provincial Highway No. 61, this study considers …
Machine learning based short-term travel time prediction: Numerical results and comparative analyses
B Qiu, W Fan - Sustainability, 2021 - mdpi.com
Due to the increasing traffic volume in metropolitan areas, short-term travel time prediction
(TTP) can be an important and useful tool for both travelers and traffic management …
(TTP) can be an important and useful tool for both travelers and traffic management …
Modal decomposition based ensemble learning for ground source heat pump systems load forecasting
C Xu, H Chen, W Xun, Z Zhou, T Liu, Y Zeng… - Energy and …, 2019 - Elsevier
This study presents a case study of office buildings using modal decomposition based
ensemble learning method to forecast energy consumption of ground source heat pump …
ensemble learning method to forecast energy consumption of ground source heat pump …
Travel time prediction for traveler information system in heterogeneous disordered traffic conditions using GPS trajectories
Precise travel time prediction allows travelers and system controllers to be aware of the
future conditions on roadways and helps in pre-trip planning and traffic control strategy …
future conditions on roadways and helps in pre-trip planning and traffic control strategy …
[HTML][HTML] An ensemble machine learning approach for the detection of unannounced meals to enhance postprandial glucose control
Background: Hybrid automated insulin delivery systems enhance postprandial glucose
control in type 1 diabetes, however, meal announcements are burdensome. To overcome …
control in type 1 diabetes, however, meal announcements are burdensome. To overcome …
Probabilistic prediction of trip travel time and its variability using hierarchical Bayesian learning
This paper proposes a probabilistic machine learning methodology to predict travel time and
its variability for trips between locations in New York City. First, a hierarchical Bayesian …
its variability for trips between locations in New York City. First, a hierarchical Bayesian …