首页|Studies from Sichuan University Provide New Data on Support Vector Machines (Res earch On Pso-svm Base Wine Grade Recognition Based On Max-relevance and Min-redu ndancy Feature Selection)
Studies from Sichuan University Provide New Data on Support Vector Machines (Res earch On Pso-svm Base Wine Grade Recognition Based On Max-relevance and Min-redu ndancy Feature Selection)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Support Vecto r Machines have been published. According to news reporting from Zigong, People’ s Republic of China, by NewsRx journalists, research stated, “In response to the challenges inherent in Baijiu classification, characterized by ambiguity and li mited methodologies, this study introduces a novel framework for comprehensive B aijiu brewing process management. By integrating mathematical models and machine learning algorithms, our aim is to standardize and enhance the accuracy of the Baijiu brewing process.” Financial support for this research came from Sichuan Provincial Transfer Paymen t Key RD Project.
ZigongPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupport Vector MachinesVector Machi nesSichuan University
NETL
NSTL
