Detection of Physical Environmental Factors on Comfortableness of Housing

Abstract

Physical environmental factors of housing are affected to emotional feeling of human being who is living in the housing. The effect of some physical environmental factors of the housing on comfortableness (emotion) against the housing itself should be precisely investigated because physical factors such as sunshine, colour of interior, temperature, sound and so on would be set in comfortable degree. In the present study, physical and sensory environmental factors against the actual housing and comfortableness factors of the housing were collected by questionnaire sheet with Visual Analog Scale method and the correlation between those factors was analyzed. Three comfortableness factors such as "Kaitekisei", "Okiniiri" and "Kenkoteki" was divided into three groups such as Comfortable("Manzoku"), Unconfortable("Fumanzoku") and Medium. When the combination analysis of physical and sensory environmental factors affecting to these three factors was performed by means of Fuzzy Neural Network, more than 90% of accuracy was obtained. The values were fairly high compared with conventional statistical analysis, such as CART and LDA. From the acquired rule, it was found that intimate feeling "Kutsurogu" as emotional environment and lighting or color of housing as housing physical environment were affected to "Kaitekisei" and "Okiniiri" and those comfortableness factors could be elucidated by the housing environment.

Combinational risk factors of metabolic syndrome identified by fuzzy neural network analysis of health-check data

“…So far, FNN has shown considerable flexibility in modeling of such complex phenomena as biochemical engineering processes (modeling of links between process valuables and process outputs) [ 11 , 12 ], food science (modeling of links between chemical components and sensory evaluation) [ 13 ], protein structural science (modeling of links between amino acid sequences and enzyme function) [ 14 ], housing science (modeling of links between physical environmental factors and human sensory evaluations) [ 15 ], and peptide science (modeling of links between peptide sequences and peptide functions) [ 16 , 17 ]. We therefore conjectured that FNN might serve as a suitable method for identifying specific characteristics that affect the pathogenesis of MetS.…”