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Environmental Control Decision Method for Livestock and Poultry House Based on Neural Networks and Improved D-S Evidence Theory

机译:基于神经网络的牲畜和家禽房的环境控制决策方法及改进的D-S证据理论

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In order to improve the accuracy of environmental control decision in livestock and poultry breeding, an environmental control decision method was designed, based on neural network and improved Dempster-Shafer (D-S) evidence theory. Firstly, the outlier data, collected by sensor, was detected and repaired using box chart method and mean substitution method. Secondly, the first-level decision classification of the data was carried out by using the neural network SoftMax multi-classification method. Finally, the improved D-S evidence theory algorithm was used to implement the final decision of the environmental control system of livestock and poultry house. Taking the environmental control system of chicken house as an example, the simulation experiment verifies the proposed method. The experimental results show that the method can make decision accurately on the environmental control system of chicken house. The proposed method has certain promotion and application value.
机译:为了提高畜禽育种环境控制决策的准确性,基于神经网络和改进的Dempster-Shafer(D-S)证据理论,设计了一种环境控制决策方法。 首先,使用传感器收集的异常值数据,并使用框图方法和均值替代方法进行修复。 其次,通过使用神经网络Softmax多分类方法执行数据的第一级别决定分类。 最后,改进的D-S证据理论算法用于实施畜禽饲养场环境控制系统的最终决定。 以鸡舍的环境控制系统为例,模拟实验验证了所提出的方法。 实验结果表明,该方法可以准确地在鸡舍的环境控制系统上做出决策。 该方法具有一定的促进和应用价值。

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