Study on Application of Multi-source Data Fusion Method in Environmental Control of Enclosed Layer House

Hualong Li, Miao Li, K. Zhan, Panpan Guo, Xianwang Liu, Xuanjiang Yang, Zhirun Ma
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Abstract

The health and laying performance of laying hens are seriously affected by the environment of enclosed layer house. At present, the environmental control system is generally based on single environmental parameters. The interaction among multiple environmental factors has not been comprehensively analyzed, which is difficult to meet the requirements of laying hens' healthy breeding. Therefore, the adaptive weighted fusion algorithm and multi-source data fusion technology were introduced into the environmental monitoring system of enclosed layer house. Firstly, the same kind of data collected by the key environmental monitoring sensors of enclosed layer house are calculated by using group adaptive fusion algorithm. Then, combined with a multi-source data fusion algorithm D-S evidence theory algorithm, the influence of the interaction of environmental parameters is analyzed, so as to improve the accuracy of environmental quality evaluation of layer house. Experiments showed that the application of multi-source data fusion algorithm in layer house environment regulation can provide decision-making results and scientific basis for accurate regulation of layer house environment, which has broad application prospects.
多源数据融合方法在封闭层屋环境控制中的应用研究
封闭式鸡舍环境严重影响蛋鸡的健康和产蛋性能。目前,环境控制系统一般是基于单一的环境参数。多种环境因素之间的相互作用尚未得到全面分析,难以满足蛋鸡健康养殖的要求。为此,将自适应加权融合算法和多源数据融合技术引入到封闭层屋环境监测系统中。首先,采用群自适应融合算法对封闭层屋关键环境监测传感器采集的同类数据进行计算;然后,结合多源数据融合算法D-S证据理论算法,分析环境参数相互作用的影响,从而提高层房环境质量评价的准确性。实验表明,将多源数据融合算法应用于分层房屋环境调控,可为分层房屋环境的精准调控提供决策结果和科学依据,具有广阔的应用前景。
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