A comparison of methods for assessing the thermal insulation value of children’s schoolwear in Kuwait

Al-Rashidi, Khaled E.; Loveday, Dennis L.; Al-Mutawa, Nawaf; Havenith, George

doi:10.1016/j.apergo.2011.05.010

Cited by 11 publications

(17 citation statements)

References 13 publications

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“…In this study, the data presented in the previous study published by Al-Rashidi et al [10] for the scholarly girl's and boy's clothing worn in Kuwait classrooms will be used to investigate the applicability of the new ANN model. Table 1 for girls and in Table 2 for boys.…”

Section: The Insulation Values Of Kuwaiti School Wearmentioning

confidence: 99%

“…In the last few decades, an observed secular change in the children's body surface area (McCullough et al [9] and Al-Rashidi et al [10]) implies that, for adolescents, the children's body surface areas are similar to those of adults, making the use of adult clothing tables even more acceptable. McCullough et al [9] and Al-Rashidi et al [10] in these studies give some evidence to support the applicability of using adults' data in [3,11] standards to assess the thermal insulation values of different children's clothing ensembles, provided that careful selection of the garments, ensembles material, and design takes place.…”

Section: Introductionmentioning

confidence: 99%

“…The objectives of this study are (1) to use the thermal insulation actual data obtained in Al-Rashidi et al [10] study to develop and design an artificial neural network model to predict the thermal insulation of the school wear in Kuwait classrooms: the data of this study were used to train, validate, and test the ANN, (2) to investigate the applicability of the new ANN model to predict the thermal insulation of different clothing ensembles.…”

Section: Introductionmentioning

confidence: 99%

“…In this study, a neural network model was developed and designed depending on the actual clothing thermal insulation data obtained by Al-Rashidi et al [10] for the different scholarly clothing used in Kuwait classrooms. The objectives of this study are (1) to use the thermal insulation actual data obtained in Al-Rashidi et al [10] study to develop and design an artificial neural network model to predict the thermal insulation of the school wear in Kuwait classrooms: the data of this study were used to train, validate, and test the ANN, (2) to investigate the applicability of the new ANN model to predict the thermal insulation of different clothing ensembles.…”

Section: Introductionmentioning

confidence: 99%

“…In a comprehensive study done by Al-Rashidi et al [10] three methods were used to determine the thermal insulation values of summer and winter school clothing ensembles worn by 6-to 17-year-old school children, girls and boys, in Kuwait classrooms. The insulation of the different clothing ensembles was determined by measurement using adult-sized versions of the clothing on thermal manikins, estimations from adult clothing data obtained from the standards tables in [3,11], and calculations using a regression equation from McCullough et al [8] that was adapted by Havenith [4] to accommodate children's sizes.…”

Section: Introductionmentioning

confidence: 99%

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Artificial Neural Network Estimation of Thermal Insulation Value of Children’s School Wear in Kuwait Classroom

Al-Rashidi¹,

Alazmi

2015

Advances in Artificial Neural Systems

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Artificial neural network (ANN) was utilized to predict the thermal insulation values of children's school wear in Kuwait. The input thermal insulation data of the different children's school wear used in Kuwait classrooms were obtained from study using thermal manikins. The lowest mean squared error (MSE) value for the validation data was 1.5 × 10 −5 using one hidden layer of six neurons and one output layer. The R 2 values for the training, validation, and testing data were almost equal to 1. The values from ANN prediction were compared with McCullough's equation and the standard tables' methods. Results suggested that the ANN is able to give more accurate prediction of the clothing thermal insulation values than the regression equation and the standard tables methods. The effect of the different input variables on the thermal insulation value was examined using Garson algorithm and sensitivity analysis and it was found that the cloths weight, the body surface area nude (BSA 0 ), and body surface area covered by one layer of clothing (BSAC 1 ) have the highest effect on the thermal insulation value with about 29%, 27%, and 23%, respectively.

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Section: The Insulation Values Of Kuwaiti School Wearmentioning

confidence: 99%