title: A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system.
abstract: Ammonia (NH3) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human's vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with "Gbell" membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R2) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.
authors.affiliation: Institute of Information Technology, Heilongjiang Bayi Agricultural University, Daqing 163319, China. Electronic address: xqj197610@163.com.
authors.forename: Qiuju
authors.initials: Q
authors.lastname: Xie
authors.affiliation: Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA.
authors.forename: Ji-Qin
authors.initials: JQ
authors.lastname: Ni
authors.affiliation: Institute of Electric and Information, Northeast Agricultural University, Harbin 150030, China.
authors.forename: Zhongbin
authors.initials: Z
authors.lastname: Su
mesh_terms: D000393:Air Pollutants / Q000032:analysis; D000465:Algorithms; D000641:Ammonia / Q000032:analysis*; D000822:Animal Husbandry / Q000379:methods; D000818:Animals; D001185:Artificial Intelligence; D005160:Facility Design and Construction; D017143:Fuzzy Logic; D005740:Gases; D006813:Humidity; D016014:Linear Models; D016571:Neural Networks, Computer; D012044:Regression Analysis; D013552:Swine; D013696:Temperature; D013850:Thinking; D014691:Ventilation
chemical_list: D000393:Air Pollutants; D005740:Gases; D000641:Ammonia
keywords: Adaptive neuro fuzzy inference system; Air quality; Ammonia concentration; Emissions; Prediction