Air quality monitoring of sow houses with the fuzzy comprehensive evaluation method

Abstract

AbstractThe comfort of sow house environments is dependent on several aspects. Therefore, it is difficult to accurately assess and control the environment by applying a single factor. In this study, Shannon's entropy theory, the fuzzy comprehensive evaluation (FCE) method, as well as the improved analytic hierarchy process (IAHP) were combined to provide reasonable subjective and objective weights for environmental comfort evaluation modeling. In addition, an evaluation index system including five environmental factors was established. To decide the membership degree of each environmental factor, we proposed a method to establish fuzzy membership functions (MFs) and devised a calculation method for related parameters. Three basic types of MFs, including the trapezoidal membership function (trapmf), pi‐shaped membership function (pimf), and ridge membership function (ridgemf), were adopted to establish an evaluation model that fit well with the entropy‐IAHP‐FCE model. The proposed method was verified using real measurements of spatiotemporal data, and results show that multiple environmental parameters were successfully integrated into the FCE for sow house environment evaluation. The FCE method delivered higher correlation coefficients of 0.8785, 0.9512, and 0.9719 compared with the temperature‐humidity index, single‐factor evaluation, and least squares support vector regression methods. The FCE method enhances sensitivity and performs an effective evaluation of environmental comfort. It can be integrated into environmental control and early‐warning systems for environmental management optimization, thereby enhancing sow production and welfare.