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Optimization of Temperature and Relative Humidity in an Automatic Egg Incubator Using Mamdani Fuzzy Inference System

机译:Mamdani模糊推理系统自动蛋孵化器中温度和相对湿度的优化

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Temperature and humidity are two of the rudimentary factors that must be controlled during egg incubation. Improper temperature and humidity levels during the incubation period often result in unwanted conditions. This paper proposes the design of an efficient Mamdani fuzzy inference system instead of the widely used Takagi-Sugeno system in this field for controlling the temperature and humidity levels of an egg incubator. Though the optimum incubation temperature and humidity levels used here are that of chicken egg, the proposed methodology is applicable to other avian species as well. The input functions have been used here as per estimated values for safe hatching using Mamdani whereas defuzzification method, Center of Area (COA), has been applied for output. From the model output, a stabilized heat from temperature level and fan speed to control the humidity level of an egg incubator can be obtained. This maximizes the hatching rate of healthy chicks under any conditions in the field.
机译:温度和湿度是在蛋孵育期间必须控制的两个基本因素。潜伏期期间的温度和湿度水平不正常导致不需要的条件。本文提出了一种高效的Mamdani模糊推理系统的设计,而不是在该领域中广泛使用的Takagi-Sugeno系统,用于控制蛋培养箱的温度和湿度水平。虽然这里使用的最佳孵化温度和湿度水平是鸡蛋,但该方法也适用于其他禽类。此处已经使用了输入功能,根据使用Mamdani的安全孵化的估计值,而Defuzzification方法,面积中心(COA),已应用于输出。从模型输出,可以获得来自温度水平和风扇速度的稳定热量来控制蛋培养箱的湿度水平。这使得在场的任何条件下最大化了健康雏鸡的孵化率。

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