%0 Journal Article %1 Muruga_2015 %A Raja, A.P.Jaya Muruga %A V.Meenakshi, %D 2015 %I Auricle Technologies, Pvt., Ltd. %J International Journal on Recent and Innovation Trends in Computing and Communication %K Backpropagation dimming illuminance level luminaires. network neural training zoning %N 2 %P 438--443 %R 10.17762/ijritcc2321-8169.150203 %T Neural Network Based Dimming Level Control of LED Network %U http://dx.doi.org/10.17762/ijritcc2321-8169.150203 %V 3 %X Energy crisis is one of the major problems faced by many countries in the world which hinder their development process as energy supply forms the basis of production of goods in various fields. Production of energy and its conservation plays a vital role in ascending the steps towards development. Avoiding wastage of energy and conserving is equally importance as production of the same. Energy utilized for lighting purpose sums up to a considerable part in the overall energy consumed. Effective and efficient lighting helps in reducing the unwanted excessive energy that is wasted. Smart illuminance control techniques concentrates on providing effective illuminance at a work place by varying the dimming levels of the networked luminaires. Many conventional illuminance control methods are available such as open loop control approach, closed loop control approach, zoning approach etc. A neural network based illuminance control strategy is proposed in this paper in which a back propagation algorithm is used to train the neural network based controller that effectively controls the dimming levels of the networked luminaires to provide required luminance at the workspace

@article{Muruga_2015, abstract = {Energy crisis is one of the major problems faced by many countries in the world which hinder their development process as energy supply forms the basis of production of goods in various fields. Production of energy and its conservation plays a vital role in ascending the steps towards development. Avoiding wastage of energy and conserving is equally importance as production of the same. Energy utilized for lighting purpose sums up to a considerable part in the overall energy consumed. Effective and efficient lighting helps in reducing the unwanted excessive energy that is wasted. Smart illuminance control techniques concentrates on providing effective illuminance at a work place by varying the dimming levels of the networked luminaires. Many conventional illuminance control methods are available such as open loop control approach, closed loop control approach, zoning approach etc. A neural network based illuminance control strategy is proposed in this paper in which a back propagation algorithm is used to train the neural network based controller that effectively controls the dimming levels of the networked luminaires to provide required luminance at the workspace}, added-at = {2015-08-04T06:24:36.000+0200}, author = {Raja, A.P.Jaya Muruga and V.Meenakshi}, biburl = {https://www.bibsonomy.org/bibtex/2b78603ae93db8cbca6899f5b0f99161d/ijritcc}, doi = {10.17762/ijritcc2321-8169.150203}, interhash = {aa144c5b0dd939b0810319ec812b6101}, intrahash = {b78603ae93db8cbca6899f5b0f99161d}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {Backpropagation dimming illuminance level luminaires. network neural training zoning}, month = {february}, number = 2, pages = {438--443}, publisher = {Auricle Technologies, Pvt., Ltd.}, timestamp = {2015-08-04T06:24:36.000+0200}, title = {Neural Network Based Dimming Level Control of {LED} Network}, url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150203}, volume = 3, year = 2015 }