An Artificial Neural Network for Analyzing Overall Uniformity in Outdoor Lighting Systems

Abstract

Street lighting installations are an essential service for modern life due to their capability of creating a welcoming feeling at nighttime. Nevertheless, several studies have highlighted that it is possible to improve the quality of the light significantly improving the uniformity of the illuminance. The main difficulty arises when trying to improve some of the installation's characteristics based only on statistical analysis of the light distribution. This paper presents a new algorithm that is able to obtain the overall illuminance uniformity in order to improve this sort of installations. To develop this algorithm it was necessary to perform a detailed study of all the elements which are part of street lighting installations. Because classification is one of the most important tasks in the application areas of artificial neural networks, we compared the performances of six types of training algorithms in a feed forward neural network for analyzing the overall uniformity in outdoor lighting systems. We found that the best algorithm that minimizes the error is "Levenberg-Marquardt back-propagation", which approximates the desired output of the training pattern. By means of this kind of algorithm, it is possible to help to lighting professionals optimize the quality of street lighting installations.

A comparative analysis of artificial neural network architectures for building energy consumption forecasting

“…the number of hidden layers (HLs), number of hidden nodes, activation functions, number of epochs, learning rate, batch size, optimizers, loss function, and so on) to specify the structure of the network itself or to determine how to train neural networks (NN). 36,37 Of these, the two most essential hyperparameters are the activation function and the number of HLs. 37 Activation functions assist the network in separating useful data from noise [38][39][40][41] and are also used to introduce nonlinearity to models, which allows ANN models to learn nonlinear prediction boundaries.…”

Maintenance Factor Identification in Outdoor Lighting Installations Using Simulation and Optimization Techniques

“…They account for up to 2.3% of the global electricity consumption [14,15]. Moreover, high-quality outdoor lighting is an essential service for a city; it has economic benefits for municipalities, engenders a feeling of safety for inhabitants, aids the vision of drivers and pedestrians and contributes to energy efficiency [14,16,17]. Therefore, lighting optimization is an important field of study in modern society and several authors have carried out extensive research on this issue [2,14,[16][17][18][19].…”

“…Currently, street and road lighting facilities are one of the highest energy consumers owing to their inefficiency. They account for up to 2.3% of the global electricity consumption [14,15]. Moreover, high-quality outdoor lighting is an essential service for a city; it has economic benefits for municipalities, engenders a feeling of safety for inhabitants, aids the vision of drivers and pedestrians and contributes to energy efficiency [14,16,17].…”

“…Gago-Calderón et al [17] studied LED photometric properties such as illuminance, uniformity, disability and discomfort glares and enhanced these properties by using an improved optic cover. Corte-Valiente et al [14] presented a new algorithm to optimize street lighting installations by obtaining the overall illuminance uniformity. They found that the Levenberg-Marquardt back-propagation algorithm was the best at minimizing the error.…”

“…Moreover, high-quality outdoor lighting is an essential service for a city; it has economic benefits for municipalities, engenders a feeling of safety for inhabitants, aids the vision of drivers and pedestrians and contributes to energy efficiency [14,16,17]. Therefore, lighting optimization is an important field of study in modern society and several authors have carried out extensive research on this issue [2,14,[16][17][18][19]. Nardelli et al [2] evaluated the potential of LED technology and their results showed that LED light sources have an extensive lifecycle, good luminous efficiency and superior color rendering index, although the acquisition costs are still high.…”