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Evolving fuzzy neural hydrocarbon networks : a model based on organic compounds
(Elsevier B.V., 2020-09)
This paper presents a new evolving intelligent model capable of combining the techniques and concepts of artificial neural networks, fuzzy systems and artificial hydrocarbon networks, in which the latter aggregates concepts ...
A novel artificial hydrocarbon networks based value function approximation in hierarchical reinforcement learning
(Springer Verlag, 2017)
Reinforcement learning aims to solve the problem of learning optimal or near-optimal decision-making policies for a given domain problem. However, it is known that increasing the dimensionality of the input space (i.e. ...
An indoor predicting climate conditions approach using Internet-of-things and artificial hydrocarbon networks
(Elsevier B.V., 2019)
The prediction and understanding of environmental conditions are of great importance to prevent and analyze changes in environment, supporting meteorological based sectors, such as agriculture or smart cities. In that ...
Stochastic parallel extreme artificial hydrocarbon networks : an implementation for fast and robust supervised machine learning in high-dimensional data
(Elsevier Ltd., 2020-03)
Artificial hydrocarbon networks (AHN) – a supervised learning method inspired on organic chemical structures and mechanisms – have shown improvements in predictive power and interpretability in comparison with other ...
Doubly fed induction generator (DFIG) wind turbine controlled by artificial organic networks
(Springer Verlag, 2017)
The main goal of this paper is to show the control capabilities of artificial organic networks when they are applied to variable speed wind generators. Since doubly fed induction generator (DFIG) is one of the most important ...
Design and equilibrium control of a force-balanced one-leg mechanism
(Springer Verlag, 2018)
The problem of equilibrium is critical for planning, control, and analysis of legged robot. Control algorithms for legged robots use the equilibrium criteria to avoid falls. The computational efficiency of the equilibrium ...
A novel wearable sensor-based human activity recognition approach using artificial hydrocarbon networks
(MDPI AG, 2016)
Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of ...
Versatility of artificial hydrocarbon networks for supervised learning
(Springer Verlag, 2019)
Surveys on supervised machine show that each technique has strengths and weaknesses that make each of them more suitable for a particular domain or learning task. No technique is capable to tackle every supervised learning ...
A reinforcement learning method for continuous domains using artificial hydrocarbon networks
(Institute of Electrical and Electronics Engineers Inc., 2018)
Reinforcement learning in continuous states and actions has been limitedly studied in ocassions given difficulties in the determination of the transition function, lack of performance in continuous-to-discrete relaxation ...
Human activity recognition on mobile devices using artificial hydrocarbon networks
(Springer Verlag, 2018)
Human activity recognition (HAR) aims to classify and identify activities based on data-driven from different devices, such as sensors or cameras. Particularly, mobile devices have been used for this recognition task. ...