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To design and manage office buildings that are both energy-efficient and productive work environments, we need a better understanding of the relationship between building and occupant systems. Past data-driven building research has focused on energy effici ...
There have been many advances in the field of reinforcement learning in continuous control problems. Usually, these approaches use deep learning with artificial neural networks for approximation of policies and value functions. In addition, there have been ...
Humans and some other animals are able to perform tasks that require coordination of movements across multiple temporal scales, ranging from hundreds of milliseconds to several seconds. The fast timescale at which neurons naturally operate, on the order of ...
Reflection is a fuzzy concept. In this article we reveal the paradoxes involved in studying the nature of reflection. Whereas some scholars emphasize its discursive nature, we go further and underline its resemblance to the self-biased dialogue Socrates ha ...
This study proposes a new technique for real-time building energy modelling and event detection using kernel regression. We show that this technique can exceed the performance of conventional neural network algorithms, and do so by a large margin when the ...
Improving the energy sustainability of our cities involves the integration of multiple renewable energy technologies into existing energy infrastructure, stretching the capabilities of traditional energy systems to the limit. To consider the transition tak ...
Human gait analysis and classification is the process of identifying individuals by their walking manners. Computerized gait analysis using neural networks and fuzzy logic has become an integral part of the treatment decision-making process. Authors propos ...
The novelty this article brings is the use of neural networks and neuro-fuzzy modeling to take the engine knock detection based on pressure and vibration samples taken from an internal combustion engine to the next step from previous achievements, the ulti ...
This paper presents a digital, transistor level implemented neo-fuzzy neural network. This type of neural network is particularly well suited for real-time applications like those encountered in signal processing and nonlinear system identification. We con ...
Mobility is a central aspect of our life; the locations we visit reflect our tastes and lifestyle and shape our social relationships. The ability to foresee the places a user will visit is therefore beneficial to numerous applications, ranging from forecas ...
