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Proceedings of the Pacific Rim Statistical Conference for Production Engineering: Big Data, Production Engineering and Statistics 2018 ed. [Kõva köide]

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  • Formaat: Hardback, 170 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 29 Illustrations, color; 7 Illustrations, black and white; VIII, 170 p. 36 illus., 29 illus. in color., 1 Hardback
  • Sari: ICSA Book Series in Statistics
  • Ilmumisaeg: 28-Mar-2018
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811081670
  • ISBN-13: 9789811081675
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Proceedings of the Pacific Rim Statistical Conference for Production Engineering: Big Data, Production Engineering and Statistics 2018 ed.Suurem pilt
  • Formaat: Hardback, 170 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 29 Illustrations, color; 7 Illustrations, black and white; VIII, 170 p. 36 illus., 29 illus. in color., 1 Hardback
  • Sari: ICSA Book Series in Statistics
  • Ilmumisaeg: 28-Mar-2018
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811081670
  • ISBN-13: 9789811081675
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789811081675.html
Märksõnad:
This book presents the proceedings of the 2nd Pacific Rim Statistical Conference for Production Engineering: Production Engineering, Big Data and Statistics, which took place at Seoul National University in Seoul, Korea in December, 2016. The papers included discuss a wide range of statistical challenges, methods and applications for big data in production engineering, and introduce recent advances in relevant statistical methods.
Part I Design and Collection of Big Data
1 Bottom-Up Estimation and Top-Down Prediction: Solar Energy Prediction Combining Information from Multiple Sources
3(12)
Youngdeok Hwang
Siyuan Lu
Jae-Kwang Kim
2 The 62% Problems of SN Ratio and New Conference Matrix for Optimization: To Reduce Experiment Numbers and to Increase Reliability for Optimization
15(8)
Teruo Mori
Part II Analytic Methods of Big Data
3 Possible Clinical Use of Big Data: Personal Brain Connectomics
23(10)
Dong Soo Lee
4 The Real-Time Tracking and Alarming the Early Neurological Deterioration Using Continuous Blood Pressure Monitoring in Patient with Acute Ischemic Stroke
33(8)
Youngjo Lee
Maengseok Noh
Il Do Ha
Part III Operation/Production Decision Making
5 Condition Monitoring and Operational Decision-Making in Modern Semiconductor Manufacturing Systems
41(26)
Dragan Djurdjanovic
6 Multistage Manufacturing Processes: Innovations in Statistical Modeling and Inference
67(18)
Hsiang-Ling Hsu
Ching-Kang Ing
Tze Leung Lai
Shu-Hui Yu
Part IV Reliability and Health Management
7 Recent Research in Dynamic Screening System for Sequential Process Monitoring
85(10)
Peihua Qiu
Lu You
8 Degradation Analysis with Measurement Errors
95(30)
Chien-Yu Peng
Hsueh-Fang Ai
Part V Recent Advances in Statistical Methods
9 A Least Squares Method for Detecting Multiple Change Points in a Univariate Time Series
125(20)
Kyu S. Hahn
Won Son
Hyungwon Choi
Johan Lim
10 Detecting the Change of Variance by Using Conditional Distribution with Diverse Copula Functions
145(10)
Jong-Min Kim
Jaiwook Baik
Mitch Reller
11 Clustering Methods for Spherical Data: An Overview and a New Generalization
155(10)
Sungsu Kim
Ashis SenGupta
12 A Semiparametric Inverse Gaussian Model and Inference for Survival Data
165
Sangbum Choi