在机器学习和模式识别中,降维能够显著提升分类器的判别性能与效率。比率和(ratio sum,RS)是线性判别分析(linear discriminant analysis,LDA)的一种全新变体,它试图使投影矩阵在每个维度上都达到最优。但RS并没有考虑到数据的局部几何...在机器学习和模式识别中,降维能够显著提升分类器的判别性能与效率。比率和(ratio sum,RS)是线性判别分析(linear discriminant analysis,LDA)的一种全新变体,它试图使投影矩阵在每个维度上都达到最优。但RS并没有考虑到数据的局部几何结构,这就可能导致无法求得最优解。为了克服RS的这一缺点,提出了一种自适应近邻局部比值和线性判别分析算法(adaptive neighbor local ratio sum linear discriminant analysis,ANLRSLDA)。该算法使用自适应近邻的构图方法构建邻接矩阵,保留数据的局部几何结构完成了数据类间及类内矩阵的构建,从而更好地找到数据的最优表示;并且该方法采用有效的无核参数邻域分配策略来构造邻接矩阵,避免调整热核参数的需要。在UCI数据集及人脸数据集进行了对比实验,验证了该算法的有效性。展开更多
In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and comp...In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and complex structure),the aircraft control system contains several uncertainties,such as imprecision,incompleteness,redundancy and randomness.The information fusion technology is usually used to solve the uncertainty issue,thus improving the sampled data reliability,which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system.In this work,we first analyze the uncertainties in the aircraft control system,and also compare different uncertainty quantitative methods.Since the information fusion can eliminate the effects of the uncertainties,it is widely used in the fault diagnosis.Thus,this paper summarizes the recent work in this aera.Furthermore,we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system.Finally,this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.展开更多
文摘在机器学习和模式识别中,降维能够显著提升分类器的判别性能与效率。比率和(ratio sum,RS)是线性判别分析(linear discriminant analysis,LDA)的一种全新变体,它试图使投影矩阵在每个维度上都达到最优。但RS并没有考虑到数据的局部几何结构,这就可能导致无法求得最优解。为了克服RS的这一缺点,提出了一种自适应近邻局部比值和线性判别分析算法(adaptive neighbor local ratio sum linear discriminant analysis,ANLRSLDA)。该算法使用自适应近邻的构图方法构建邻接矩阵,保留数据的局部几何结构完成了数据类间及类内矩阵的构建,从而更好地找到数据的最优表示;并且该方法采用有效的无核参数邻域分配策略来构造邻接矩阵,避免调整热核参数的需要。在UCI数据集及人脸数据集进行了对比实验,验证了该算法的有效性。
基金supported by the National Natural Science Foundation of China(62273176)the Aeronautical Science Foundation of China(20200007018001)the China Scholarship Council(202306830096).
文摘In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and complex structure),the aircraft control system contains several uncertainties,such as imprecision,incompleteness,redundancy and randomness.The information fusion technology is usually used to solve the uncertainty issue,thus improving the sampled data reliability,which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system.In this work,we first analyze the uncertainties in the aircraft control system,and also compare different uncertainty quantitative methods.Since the information fusion can eliminate the effects of the uncertainties,it is widely used in the fault diagnosis.Thus,this paper summarizes the recent work in this aera.Furthermore,we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system.Finally,this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.
文摘通过数字化技术整合文字、图片、视频及三维动画等教学资源,构建基于智能手机微信小程序的数字化口腔解剖生理-牙体形态结构学习平台,展示牙齿三维数字模型.参照人民卫生出版社教材《口腔解剖生理学》(第七版)及Wheeler's Dental Anatomy,Physiology and Occlusion对牙体结构形态部分进行文字编排.通过对离体牙进行拍摄、锥形束CT扫描后获得牙齿外型JPEG文件和牙体横断面的DICOM文件,后期采用Photoshop CS6、CS 3D imaging(锥形束CT附带的简略版软件)、Snagit、Video Editor及爱剪辑5个软件制作牙体连续断层解剖动态图及各牙体3D展示视频.按照微信官网小程序开发的步骤进行注册、开发、编写代码,将图片和文字导入,提交审核和发布等.完成'牙体解剖学习平台'微信小程序制作并投入使用.90.3%(93人)的使用者认为其对学习《口腔解剖生理学》有帮助,特别在加深对牙齿形态结构的理解和记忆牙齿形态结构的知识点方面.96.1%(99人)的使用者认为小程序应该加入课堂作为口腔专业学生学习的补充,但不认为其可取代课本.'牙体解剖学习平台'微信小程序的开发将为口腔各类教学资源基于网络开发整合提供方法学的借鉴.
