Dynamic monitoring and predictive modeling in animal health management
In recent years,the frequent occurrence of animal diseases and climate change have exacerbated the complexity of an-imal health management,forcing the industry to adopt more efficient technological means to meet these challenges.The current status of dynamic monitoring and predictive modeling in animal health management is discussed,and the innovative development of physiological indicator monitoring,behavioral monitoring,and environmental factor monitoring combined with data acquisition and processing technologies currently applied in animal health management is introduced.Subsequently,the application of predic-tive models based on machine learning and time series analysis in animal disease prediction is analyzed,and the dynamic adjust-ment and feedback mechanism is further explored.It is concluded that dynamic monitoring and prediction models have significant advantages in improving the efficiency of animal health management and reducing the risk of epidemics,while there are limitations in data privacy,security issues and maintainance.
animal health managementdynamic monitoring systempredictive modelingmachine learningtime series analysis
万方数据
维普
