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 …
Dynamic classifier selection: Recent advances and perspectives
Abstract Multiple Classifier Systems (MCS) have been widely studied as an alternative for
increasing accuracy in pattern recognition. One of the most promising MCS approaches is …
increasing accuracy in pattern recognition. One of the most promising MCS approaches is …
[HTML][HTML] A dynamic ensemble learning algorithm for neural networks
This paper presents a novel dynamic ensemble learning (DEL) algorithm for designing
ensemble of neural networks (NNs). DEL algorithm determines the size of ensemble, the …
ensemble of neural networks (NNs). DEL algorithm determines the size of ensemble, the …
Modified Alexnet architecture for classification of diabetic retinopathy images
T Shanthi, RS Sabeenian - Computers & Electrical Engineering, 2019 - Elsevier
Diabetic retinopathy (DR) is an illness occurring in the eye due to increase in blood glucose
level. Among people in the age group of 70, 50% of deaths are attributed to diabetes. Early …
level. Among people in the age group of 70, 50% of deaths are attributed to diabetes. Early …
[HTML][HTML] Flood detection and susceptibility mapping using sentinel-1 remote sensing data and a machine learning approach: Hybrid intelligence of bagging ensemble …
Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we
propose a new flood susceptibility mapping technique. We employ new ensemble models …
propose a new flood susceptibility mapping technique. We employ new ensemble models …
[图书][B] Ensemble methods: foundations and algorithms
ZH Zhou - 2012 - books.google.com
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach,
Ensemble Methods: Foundations and Algorithms shows how these accurate methods are …
Ensemble Methods: Foundations and Algorithms shows how these accurate methods are …
A survey of multiple classifier systems as hybrid systems
A current focus of intense research in pattern classification is the combination of several
classifier systems, which can be built following either the same or different models and/or …
classifier systems, which can be built following either the same or different models and/or …
State of charge estimation for Li-ion batteries using neural network modeling and unscented Kalman filter-based error cancellation
Lithium-ion batteries have been widely used as the energy storage systems in personal
portable electronics (eg cell phones, laptop computers), telecommunication systems, electric …
portable electronics (eg cell phones, laptop computers), telecommunication systems, electric …
[图书][B] Combining pattern classifiers: methods and algorithms
LI Kuncheva - 2014 - books.google.com
A unified, coherent treatment of current classifier ensemble methods, from fundamentals of
pattern recognition to ensemble feature selection, now in its second edition The art and …
pattern recognition to ensemble feature selection, now in its second edition The art and …