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| Prediction of ammonia concentration in piggery based on ARIMA and BP neural network |
| LIU Chun-hong1,2, YANG Liang1, DENG He1, GUO Yu-chen1, LI Dao-liang1,2, DUAN Qing-ling1,2 |
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;
2. Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, Beijing 100083, China |
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Abstract In order to reduce ammonia emissions from the source during pig breeding and reduce the ammonia concentration in piggery, this paper proposed a combination prediction method based on ARIMA-BP neural network for the concentration of ammonia in piggery, and compared with the combined prediction method based on ARIMA-BP neural network, from the perspective of optimal weight and residual optimization. The proposed prediction method was applied to the prediction of ammonia concentration in a piggery in Yixing, Jiangsu province. The results of the prediction experiments showed that the prediction accuracy of the combination prediction method based on ARIMA-BP neural network residual optimization was the highest. Compared with the BP neural network, ARIMA prediction method and the optimal weight combination prediction method based on the ARIMA-BP neural network, the evaluation indexes MAE, MAPE and RMSE were 0.0319, 0.1580% and 0.0365respectively.The ammonia prediction method proposed in this paper can be used as a scientific basis for the precise control and management of piggery environment in order to reduce the ecological environmental pollution caused by ammonia emission from piggery.
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Received: 07 September 2018
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| [1] |
于洪康,吴建寨,王亚辉,等.我国生猪养殖产业现状、模式与区域布局分析[J]. 中国猪业, 2018,(1):23-26.Yu H K, Wu J Z, Wang Y H. Analysis on the current situation, model and regional distribution of pig breeding industry in China[J]. China Swine Industry, 2018,(1):23-26.
|
| [2] |
李新建,吕刚,任广志.影响猪场氨气排放的因素及控制措施[J]. 家畜生态学报, 2012,33(1):86-93.Li X J, Lv G, Ren G Z. Influencing factors of ammonia emissions from pig houses and mitigation techniques[J]. Acta Ecologiae Animalis Domastici, 2012,33(1):86-93.
|
| [3] |
程龙,郭秀锐,程水源,等.京津冀农业源氨排放对PM2.5的影响[J]. 中国环境科学, 2018,38(4):1579-1588.Cheng L, Guo X R, Cheng S Y, et al. Effect of ammonia emission from agriculture in Beijing-Tianjin-Hebei on PM2.5[J]. China Environmental Science, 2018,38(4):1579-1588.
|
| [4] |
武志敏,郑炜,任永鑫,等.北方规模化猪场周环境空气中NH3的监测分析[J]. 中国兽医杂志, 2017,53(9):91-93.Wu Z M, Zheng W, Ren Y X, et al. Monitoring analysis on ammonia of the air around pig farm in the northeast[J]. Chinese Journal of Veterinary Medicine, 2017,53(9):91-93.
|
| [5] |
王悦,赵同科,邹国元,等.畜禽养殖舍氨气排放特性及减排技术研究进展[J]. 动物营养学报, 2017,29(12):4249-4259.Wang Y, Zhao T K, Zou G Y, et al. Research statues of ammonia emission characteristics and mitigation technologies from livestock houses[J]. Chinese Journla of Animal Nutrition, 2017,29(12):4249-4259.
|
| [6] |
朱海生,董红敏.猪舍氨气排放预测模型的研究现状[J]. 农业工程学报, 2006,22(S2):187-192.Zhu H S, Dong H M. Research progress of models for predicting ammonia emision in swine houses[J]. Transcations of the CSAE, 2006, 22(S2):187-192.
|
| [7] |
Yu S H, Zhang J F, Ou J Y. Quantitative detection model of pernicious gases in pig house based on BP neural network[J]. Animal Husbandry and Feed Science, 2009,1(3):40-43,48.
|
| [8] |
Canh T T, Aarnink A J A. Influence of electrolyte balance and acidifying calcium salts in the diet of growing-finishing pigs On urinary pH, slurry pH and ammonia volatilization from slurry[J]. Livestock Production Science, 1998,56:1-13.
|
| [9] |
彭红芳.不同季节不同类型猪舍环境参数监测及对仔猪生产性能影响的研究[D]. 保定:河北农业大学, 2015.Peng H F. Monitoring of the Environmental parameter of different seasons and different types pig house and the effect on the production performance of piglets.[D]. Baoding:Agricultural University of Heibei, 2014.
|
| [10] |
许稳,刘学军,孟令敏,等.不同养殖阶段猪舍氨气和颗粒物污染特征及其动态[J]. 农业环境科学学报, 2018,37(6):1248-1254.Xu W, Liu X J, Meng L M, et al. Dynamics and pollution features of ammonia and particulate matter during different pig breeding stages[J]. Journal of Agro-Environment Science, 2018,37(6):1248-1254.
|
| [11] |
汪开英,代小蓉,李震宇,等.不同地面结构的育肥猪舍NH3排放系数[J]. 农业机械学报, 2010,41(1):163-166.Wang K Y, Dai X R, Li Z Y, et al. NH3 Emission factor of fattening pig buildings with different floor systems[J].Transactions of the Chinese Socity for Agricultural Machinery, 2010,41(1):163-166.
|
| [12] |
Lowry A. Harper, Ron R. Sharpe, John D. Simmons. Ammonia emissions from swine houses in the Southeastern United States[J]. Journal of Environment Quality, 2004,33:449-457.
|
| [13] |
Michael J H, Anders Peter S A, Poul P, et al. Prediction of odor from pig production based on chemical odorants[J]. Journal of Environment Quality, 2012,41(2):436-443.
|
| [14] |
Patra A K. Prediction of enteric methane emission from cattle using linear and non-linear statistical models in tropical production systems[J]. Mitigation and Adaptation Strategies for Global Change, 2017, 22(4):629-650.
|
| [15] |
周茁.生猪养殖环境监测及氨气浓度预警模型研究[D]. 长沙:湖南农业大学, 2014.Zhou Z. Research of pig breeding environment monitoring and early warning model of ammonia concentration[D]. Changsha:Hunan Agricultural University, 2014.
|
| [16] |
Rafiu O Y, Zainura Z N, Ahmad H A, et al. Predicting methane emissions from livestock in Malaysia using the ARIMA model[J]. Management of Environmental Quality An International Journal, 2014,25(5):584-599.
|
| [17] |
Sun G, Hoff S J, Zelle, B C, et al. Development and comparison of backpropagation and generalized regression neural network models to predict diurnal and seasonal gas and PM10 concentrations and emissions from swine buildings[J]. Transactions of the ASABE, 2008, 51(2):685-694.
|
| [18] |
俞守华,张洁芳,区晶莹.基于BP神经网络的猪舍有害气体定量检测模型研究[J]. 安徽农业科学研究, 2009,37(23):11316-11317.Yu S H, Zhang J F, Qu J Y. Quantitative detection model of pernicious gases in pig house based on BP neural network[J]. Journal of Anhui Agricultural Sciences, 2009,37(23):11316-11317.
|
| [19] |
Lidija J S, Davor Z A, MirjanaD R, et al. Modeling of methane emissions using artificial neural network approach[J]. Journal of the Serbian Chemical Society, 2015,80(3):421-433.
|
| [20] |
Roberto B, Tamara A, Antonio O, et al. Prediction of carbon dioxide concentration in weaned piglet buildings by wavelet neural network models[J]. Computers and Electronics in Agriculture, 2017,(143):201-207.
|
| [21] |
谢秋菊,罗文博,李妍,等.基于神经网络猪舍氨气浓度预测方法研究[J]. 东北农业大学学报, 2016,47(10):83-92.Xie Q J, Luo W B, Li Y, et al. Study on prediction method ammonia concentrations in pig house using Neural Network[J]. Journal of Northeast Agricultural University, 2016,47(10):83-92.
|
| [22] |
Bai Y, Li Y, Wang X X, et al. Air pollutants concentrations forecasting using back propagation neural network based on wavelet decomposition with meteorological conditions[J]. Atmospheric Pollution Research, 2016,7(3):557-566.
|
| [23] |
Zhu K H, Wu S Y, Li Q. Prediction model for piggery ammonia concentration based on genetic algorithm and optimized BP neural network[J]. Metallurgical & Mining Industry, 2015,(11):6-12.
|
| [24] |
Xie Q J, Ni J Q, Su Z B. A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system[J]. Journal of Hazardous Materials, 2017,(325):301-309.
|
| [25] |
Wang F, Su H Z, Jing K. Dam safety monitoring model based on ARIMA-ANN[J]. Engineering Journal of Wuhan University, 2010, 43(5):585-588.
|
| [26] |
尧姚,陶静,李毅.基于ARIMA-BP组合模型的民航旅客运输量预测[J]. 计算机技术与发展, 2015,25(12):147-151.Yao Y, Tao J, Li Y. Prediction of civil aviation passenger transport volume based on ARIMA-BP combined model[J]. Computer Technology and Development, 2015,25(12):147-151.
|
| [27] |
张娣,景元书,李亚春,等.基于ARMA-BP集成的藻类叶绿素a预测研究[J]. 气象科学, 2015,35(3):312-316.Zhang D, Jing Y S, Li Y C, et al. Prediction on algal chlorophyll a by integrating ARIMAand BP neural network[J]. Journal of the Meteorological Sciences, 2015,35(3):312-316.
|
| [28] |
徐涛,苏瀚,杨国庆.基于空间拟合和神经网络的机场噪声预测集成模型[J]. 中国环境科学, 2016,36(4):1250-1257.Xu T, Su H, Yang G Q. Airport noise prediction ensemble model based on space fitting and neural network[J]. China Environmental Science, 2016,36(4):1250-1257.
|
| [29] |
郑剑锋,焦继东,孙力平.基于神经网络的城市内湖水华预警综合建模方法研究[J]. 中国环境科学, 2017,37(5):1872-1878.Zhang J F, Jiao J D, Sn L P. A modeling approach for early-warning of water bloom risk in urban lake based on neural network[J]. China Environmental Science, 2017,37(5):1872-1878.
|
| [30] |
Zeng Q S, Quan S P, Jin Z Q. Short-term traffic flow's forecasting by fusing BP neural network and ARIMA[J]. Journal of Zhengzhou University Engineering Science, 2015,32(4):60-3.
|
| [31] |
宋国君,国潇丹,杨啸,等.沈阳市PM2.5浓度ARIMA-SVM组合预测研究[J]. 中国环境科学, 2018,38(11):4031-4039.Song G J, Guo X D, Yang X, et al. ARIMA-SVM combination prediction of PM2.5 concentration in Shenyang[J]. China Environmental Science, 2018,38(11):4031-4039.
|
| [32] |
吴静,李振波,朱玲,等.融合ARIMA模型和GAWNN的溶解氧含量预测方法[J]. 农业机械学报, 2017,48(S1):205-210.Wu J, Li Z B, Zhu L, et al. Hybrid Model of ARIMA Model and GAWNN for dissolved oxygen content prediction[J]. Transactions of The Chinese Society of Agricultural Machinery, 2017,48(S1):205-210.
|
| [33] |
刘东君,邹志红.最优加权组合预测法在水质预测中的应用研究[J]. 环境科学学报, 2012,32(12):3128-3132.Liu D J, Zou Z H. Application of weighted combination model on forecasting water quality[J]. Acta Scientiae Circumstantiae, 2012, 32(12):3128-3132.
|
| [34] |
Wang J, Sun L, Zhao H, et al. ARIMA-BP integrated intelligent algorithm for China's consumer price index forecasting and its applications[J]. Journal of Intelligent & Fuzzy Systems, 2016,31(4):2187-2193.
|
|
|
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