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- W3092509244 abstract "Environmental change has a major impact on the performance of a poultry farm. Due to high temperature and high relative humidity, the humidex value will increase at an unprecedented rate. Later, this leads to heat stress in layer poultry farm. In such situation, the data is collected using an IoT device for which the Multiple Linear Regression algorithm is formulated to predict the heat stress level in the poultry farm. The accuracy of the model is determined using Root Mean Squared Error, R-Square and Adjusted R-Square methods. The results show that as the humidex value increases, heat stress in poultry farm increases by affecting the overall performance of the layers in a poultry farm." @default.
- W3092509244 created "2020-10-15" @default.
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- W3092509244 date "2020-08-01" @default.
- W3092509244 modified "2023-10-18" @default.
- W3092509244 title "Monitoring and Detection of Heat Stress of Layers in Poultry Farm using Multiple Linear Regression" @default.
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- W3092509244 doi "https://doi.org/10.1109/icssit48917.2020.9214130" @default.
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