[Objective] The paper was to investigate the differentiation and treatment of swine influenza and common cold in veterinary clinic.[Method] The clinical data of diseased pigs from May 2017 to May 2018 were analyzed re...[Objective] The paper was to investigate the differentiation and treatment of swine influenza and common cold in veterinary clinic.[Method] The clinical data of diseased pigs from May 2017 to May 2018 were analyzed retrospectively to explore the clinical treatment methods for swine influenza and common cold, and the effectiveness and accuracy of clinical diagnosis was further improved. [Result] Through in-depth analysis of test results, we obtained a comprehensive understanding of the main causes of swine influenza and common cold, and found that the causes in-cluded improper breeding management of pigs, nutrition of pigs and lack of immunity of newborn pigs. [Conclusion] Analysis of the causes of swine influenza and common cold and suggestion of targeted clinical treatment measures will reduce the incidence of swine disease, and promote the vet-erinary clinical treatment effect of swine influenza and common cold.展开更多
In order to improve the accuracy and reliability of ammonia(NH3)concentration prediction,which can provides a support to the ventilation control strategy,so as to reduce the impact of NH3 on the health and productivit...In order to improve the accuracy and reliability of ammonia(NH3)concentration prediction,which can provides a support to the ventilation control strategy,so as to reduce the impact of NH3 on the health and productivity of swine,this paper proposed an NH3 concentration prediction method based on Empirical Mode Decomposition(EMD)and Elman neural network modelling.The NH3 concentration and other four environmental parameters including temperature,humidity,carbon dioxide and light intensity were decomposed into several different time-scale intrinsic mode functions(IMFs).Then,the Elman neural network prediction model was used to predict each IMF.The predicted NH3 was obtained by reconstructing all the IMFs by EMD.The results show that for the proposed method,the determination coefficient between the predicted and real measured value is 0.9856,the Mean Absolute Error is 0.7088 ppm,the Root Mean Square Error is 0.9096 ppm,and the Mean Absolute Percentage Error is 0.41%.Compared with the Elman neural network,the proposed method has a good improvement in the accuracy,and provide effective parameters for the environmental monitoring of the swine house and the regulation of the NH3 concentration.展开更多
文摘[Objective] The paper was to investigate the differentiation and treatment of swine influenza and common cold in veterinary clinic.[Method] The clinical data of diseased pigs from May 2017 to May 2018 were analyzed retrospectively to explore the clinical treatment methods for swine influenza and common cold, and the effectiveness and accuracy of clinical diagnosis was further improved. [Result] Through in-depth analysis of test results, we obtained a comprehensive understanding of the main causes of swine influenza and common cold, and found that the causes in-cluded improper breeding management of pigs, nutrition of pigs and lack of immunity of newborn pigs. [Conclusion] Analysis of the causes of swine influenza and common cold and suggestion of targeted clinical treatment measures will reduce the incidence of swine disease, and promote the vet-erinary clinical treatment effect of swine influenza and common cold.
基金This research is financially supported by National Key Research and Development Program of China(2016YFD0700204-02)The“Young Talents”Project of Northeast Agricultural University(17QC20)+1 种基金Research on Attitude Fusion Zero Offset Correction and Decoupling Noise Reduction for Non-flat Production Flow Sensors,China Postdoctoral Fund(2016M601406)Central Guide to Local Science and Technology Development(ZY17C06)and The Earmarked Fund for China Agriculture Research System(No.CARS-35).The authors are grateful to anonymous reviewers for their comments.
文摘In order to improve the accuracy and reliability of ammonia(NH3)concentration prediction,which can provides a support to the ventilation control strategy,so as to reduce the impact of NH3 on the health and productivity of swine,this paper proposed an NH3 concentration prediction method based on Empirical Mode Decomposition(EMD)and Elman neural network modelling.The NH3 concentration and other four environmental parameters including temperature,humidity,carbon dioxide and light intensity were decomposed into several different time-scale intrinsic mode functions(IMFs).Then,the Elman neural network prediction model was used to predict each IMF.The predicted NH3 was obtained by reconstructing all the IMFs by EMD.The results show that for the proposed method,the determination coefficient between the predicted and real measured value is 0.9856,the Mean Absolute Error is 0.7088 ppm,the Root Mean Square Error is 0.9096 ppm,and the Mean Absolute Percentage Error is 0.41%.Compared with the Elman neural network,the proposed method has a good improvement in the accuracy,and provide effective parameters for the environmental monitoring of the swine house and the regulation of the NH3 concentration.
