- 期刊
The Identification of Dog's Identity via GM (0, N) And Regression Analysis
並列摘要
The main purpose of the paper is applied the GM (0, N) model in grey system theory to identity the same kinds of dog barking voice in difference order, and also use regression analysis to verify the final result . Firstly, the paper uses Speech Filing System software to transfer the dog voice into the eigen-value state. Secondly, use Gold Wave to filter the voice signal, and translate the value of eigen-value state into digital type, to build up the inspected dog's barking voice. Finally, through GM (0, N) model to identity the dog barking voice. And use the maximum weighting to identity which one is the most closely to the inspected dog, also use regression analysis to double check the result. Through the real example by using four differences shibu inu, show the method that in our paper is quite successfully.
延伸閱讀
- 楊姮稜、梁碩麟、蔡函儒、楊淑芳、賴秀穗、謝雨生（2004）。Retrospective Case Studies of Canine Aggressive Behavior Problems: Problem Analysis in 36 Dogs。臺灣獸醫學雜誌，30(1)，39-46。https://doi.org/10.7009/TVJ.200403.0039
- Chen, H. I., Wei, J., & Cheng, H. C. (1985). Determination of the Venous-To-Arterial Compliance Ratio in the Hindquarters of the Dog. The Chinese Journal of Physiology, 28(x), 23-33. https://www.airitilibrary.com/Article/Detail?DocID=03044920-198506-28-x-23-33-a
- 劉貞怡、許維志、李進成、楊淑芳、楊姮稜、林永昌、劉振軒（2005）。Clinical and Etiological Studies on Fifty Dogs with Seizures。臺灣獸醫學雜誌，31(2)，119-127。https://doi.org/10.7009/TVJ.200506.0119
- 洪意凡（2015）。The study of data mining for the pet owner relationship management and pet food recommendation mechanism〔碩士論文，淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2015.00216
- Cardoso, M. J. L., Fagnani, R., Cavalcante, C. Z., Zanutto, M. D. S., Júnior, A. Z., Fertonani, L. H. D. S., Calesso, J. R., Melussi, M., Costa, H. P., & Hashizume, E. Y. (2016). Blood Pressure, Serum Glucose, Cholesterol, and Triglycerides in Dogs with Different Body Scores. Veterinary Medicine International, 2016(), 132-138. https://doi.org/10.1155/2016/8675283