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首页> 外文期刊>International Journal of Sensor Networks and Data Communications >Study on Sensor Fusion for Predicting Human's Thermal Comfort Accounting for Individual Differences by Using Neural Network.
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Study on Sensor Fusion for Predicting Human's Thermal Comfort Accounting for Individual Differences by Using Neural Network.

机译:神经网络用于预测人的个体差异的热舒适性的传感器融合研究。

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This paper presents a method for utilizing sensor networks to predict human’s thermal comfort and sensation. A neural network is dynamically organized on the basis of correlations between the thermal sensation of office occupants and a number of values measured by the sensor network, and the structure of the neural network is cyclically updated. By way of an example, the air-conditioning system in an office is used. We place a number of temperature sensors and participants in this indoor environment, and conduct an experiment where the sensor readings and the thermal sensation of the participants are monitored concurrently. From the experimental results it can be seen that the various sensors are selected correctly and can be used to predict the desired system behavior.
机译:本文提出了一种利用传感器网络来预测人类的热舒适度和感觉的方法。根据办公室人员的热感觉与传感器网络测得的多个值之间的相关性,动态地组织神经网络,并周期性地更新神经网络的结构。举例来说,使用办公室中的空调系统。我们在此室内环境中放置了许多温度传感器和参与者,并进行了一项实验,其中要同时监视参与者的传感器读数和热感。从实验结果可以看出,正确选择了各种传感器,这些传感器可用于预测所需的系统行为。

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