DSpace Collection:
https://ah.lib.nccu.edu.tw/handle/140.119/43545
2024-03-29T07:36:24ZAn Average Loss Control Chart Under a Skewed Process Distribution,
https://ah.lib.nccu.edu.tw/handle/140.119/139839
題名: An Average Loss Control Chart Under a Skewed Process Distribution,
摘要: In the global market the quality of products is a crucial factor separating competitive companies within numerous industries. These firms may employ a loss function to measure the loss caused by a deviation of the quality variable from the target value. From the view of Taguchi’s philosophy, monitoring this deviation from the process target value is important, but in practice many quality data have distributions that are not normal but skewed. This paper thus develops an average loss control chart for monitoring quality loss variation under skewed distributions. We investigate the statistical properties of the proposed control chart and measure the out-of-control process detection performance of the proposed loss control charts by using the average run length. The average loss control chart illustrates the best performance in detecting of out-of-control loss location for a left-skewed process distribution and performs better than the existing median loss control chart.2022-04-12T00:00:00ZDimension reduction and visualization of symbolic interval-valued data using sliced inverse regression
https://ah.lib.nccu.edu.tw/handle/140.119/139838
題名: Dimension reduction and visualization of symbolic interval-valued data using sliced inverse regression
摘要: Sliced inverse regression (SIR) is a popular slice-based sufficient dimension reduction technique for exploring the intrinsic structure of high-dimensional data. A main goal of dimension reduction is data visualization. This chapter reviews the extension of principal component analysis (PCA) to the interval-valued data, followed by a brief description of the classic SIR. It considers different families of symbolic-numerical-symbolic approaches to extend SIR to the interval-valued data. The chapter evaluates the implemented interval SIR methods and compare the results with those of interval PCA for low-dimensional discriminative and visualization purposes by means of simulation studies. The analysis of interval-valued data usually serves as the basic principle for analyzing other types of symbolic data, such as multi-valued data, modal-valued data, and modal multi-valued data. The advantage of the distributional approaches is that the resulting symbolic covariance matrix fully utilizes all the information in the data.2022-04-12T00:00:00ZAn Average Loss Control Chart Under a Skewed Process Distribution
https://ah.lib.nccu.edu.tw/handle/140.119/130052
題名: An Average Loss Control Chart Under a Skewed Process Distribution2020-05-28T03:33:35ZA New Clustering Algorithm Based on Graph Connectivity
https://ah.lib.nccu.edu.tw/handle/140.119/130051
題名: A New Clustering Algorithm Based on Graph Connectivity
摘要: A new clustering algorithm based on the concept of graph connectivity is introduced. The idea is to develop a meaningful graph representation for data, where each resulting sub-graph corresponds to a cluster with highly similar objects connected by edge. The proposed algorithm has a fairly strong theoretical basis that supports its originality and computational efficiency. Further, some useful guidelines are provided so that the algorithm can be tuned to optimize the well-designed quality indices. Numerical evidences show that the proposed algorithm can provide a very good clustering accuracy for a number of benchmark data and has a relatively low computational complexity compared to some sophisticated clustering methods.2020-05-28T03:33:20Z