The comparison of neural network and hybrid neuro-fuzzy based inferential sensor models for space heating systems

Jassar, S.; Behan, Thomas; Zhao, Lian; Liao, Zai Yi

doi:10.1109/icsmc.2009.5346801

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…The results show that RenFIS based inferential model is accurate and robust. Conventional hybrid Neuro-Fuzzy systems perform better than neural networks [12] and compared to conventional system, RenFIS can significantly improve the performance of inferential models. The analysis results indicated that it can be employed to design control schemes.…”

Section: Heatingmentioning

confidence: 99%

Inferential control - An advanced control strategy to save energy in residential heating systems

Jassar

Liao

Sharma

2012

2012 IEEE Electrical Power and Energy Conference

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The paper presents an advanced control strategy for residential heating systems to save energy and improve indoor environment. This strategy, named inferential control method, is based on Recurrent Neuro-Fuzzy Inference System. In current practice, the control of these heating systems is based on the measurement of air temperature at one point within the building. The inferential control strategy allows for the control to be based on an estimate of the overall thermal performance, minimizing the chance of overheating (saving energy) and underheating (improving comfort) in the building. The performance of this control technology has been investigated through simulation study. The results show that the proposed control scheme can effectively maintain the temperature at setpoint, and results in energy savings and improved indoor environment.

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Section: Heatingmentioning

confidence: 99%

Inferential control - An advanced control strategy to save energy in residential heating systems

Jassar

Liao

Sharma

2012

2012 IEEE Electrical Power and Energy Conference

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“…After years of trying to find new algorithms, ANFIS is still in use, and recent applications were reported such as [38] or an application of ANFIS at sensor data processing [39] or [11]. The paper [26] presents some aspects related to the estimation of average air temperature in the built environment by using integer neural networks, ANFIS and inferential sensor models. The paper compares the results of these models, presenting their advantages and disadvantages.…”

Section: Related Workmentioning

confidence: 99%

“…Thus, a possible application of sensor networks, in a field with distributed points, is the tracking problem of a dynamic object movement between these distributed points on the field. The paper [26] presents a technical solution based on acoustic and visual sensors. Another solution for real time tracking in wireless sensor networks is presented in the paper [27].…”

Section: Related Workmentioning

confidence: 99%

Efficiency improvement in multi-sensor wireless network based estimation algorithms for distributed parameter systems with application at the heat transfer

Voloşencu

Curiac

2013

EURASIP J. Adv. Signal Process.

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This paper gives a technical solution to improve the efficiency in multi-sensor wireless network based estimation for distributed parameter systems. A complex structure based on some estimation algorithms, with regression and autoregression, implemented using linear estimators, neural estimators and ANFIS estimators, is developed for this purpose. The three kinds of estimators are working with precision on different parts of the phenomenon characteristic. A comparative study of three methods -linear and nonlinear based on neural networks and adaptive neuro-fuzzy inference system -to implement these algorithms is made. The intelligent wireless sensor networks are taken in consideration as an efficient tool for measurement, data acquisition and communication. They are seen as a "distributed sensor", placed in the desired positions in the measuring field. The algorithms are based on regression using values from adjacent and also on auto-regression using past values from the same sensor. A modelling and simulation for a case study is presented. The quality of estimation is validated using a quadratic criterion. A practical implementation is made using virtual instrumentation. Applications of this complex estimation system are in fault detection and diagnosis of distributed parameter systems and discovery of malicious nodes in wireless sensor networks.

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Monitoring of distributed parameter systems based on a sensor network and ANFIS

Voloşencu

Curiac

2010

The 2010 International Joint Conference on Neural Networks (IJCNN)

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The comparison of neural network and hybrid neuro-fuzzy based inferential sensor models for space heating systems

Cited by 5 publications

References 14 publications

Inferential control - An advanced control strategy to save energy in residential heating systems

Inferential control - An advanced control strategy to save energy in residential heating systems

Efficiency improvement in multi-sensor wireless network based estimation algorithms for distributed parameter systems with application at the heat transfer

Monitoring of distributed parameter systems based on a sensor network and ANFIS

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