A Neural Network Based Modeling of Closed Room Thermal Comfort Environmental Prediction for Sensor Hub

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Thongkhome P., Dejdumrong N.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2020

หน้าแรก: 55

หน้าสุดท้าย: 58

จำนวนหน้า: 4

ISBN: 9781728164861

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091847105&doi=10.1109%2fECTI-CON49241.2020.9158063&partnerID=40&md5=680039721eed34821d18a34bd1298a6f

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

Currently, environmental protection and intelligence system are topics of interest in smart homes and intelligent buildings. This work represents an environmental prediction study of the closed room which installed a split-type air-conditioning system and a newly designed sensor hub using a feed-forward back-propagation artificial neural network-based prediction for human thermal comfort and indirectly concerned to the growth or existence of diseases, contagious diseases and allergies. The RPROP algorithm was utilized to train the closed room environmental parameters that get from sensor hub especial relative humidity in the ANN model and validate the model by using cohen's kappa and ROC curve to represents the degree of accuracy and reliability. The result obtained from the ANN trained data agreed closely with those obtained from a sensor hub with the high perfect agreement. The benefit of the ANN-based strategy in this study could be utilized for the design of a sensor hub that can realize the adaptive adjustment of environmental parameters through the air conditioning system. © 2020 IEEE.

คำสำคัญ

Sensor Hub