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Reliability and Statistical Computing Modeling Methods and Applications 1st Edition by Hoang Pham ISBN 3030434125 9783030434120

Name: Reliability and Statistical Computing Modeling Methods and Applications 1st Edition by Hoang Pham ISBN 3030434125 9783030434120
SKU: EB-11035302
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Reliability and Statistical Computing Modeling Methods and Applications 1st Edition Hoang Pham (Editor) Digital Instant Download

Author(s): Hoang Pham (editor)

ISBN(s): 9783030434113, 3030434117

Edition: 1

File Details: PDF, 8.53 MB

Year: 2020

Language: English

SKU: EB-11035302 Category: Science (General) Tag: Hoang Pham (editor)

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Reliability and Statistical Computing Modeling Methods and Applications 1st Edition by Hoang Pham – Ebook PDF Instant Download/Delivery: 3030434125, 978-3030434120
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ISBN 10: 3030434125
ISBN 13: 978-3030434120
Author: Hoang Pham

This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing.

The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems.

Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.

Reliability and Statistical Computing Modeling Methods and Applications 1st Table of contents:

Reliability Computing

Modeling and Methods
- Predicted Reliability Modeling
- Mechanical Reliability Analysis
- Fatigue Distribution Functions
- Optimal Maintenance Models
- Maintenance Policies
- System Reliability with Simultaneous Failure on Consecutive Components

Statistical Computing

Modeling and Methods
- Wearable Sensor Data-Based Human Activity Recognition Using Machine Learning
- Bootstrap Confidence Interval for Regression Coefficients
- Run Rules Control Charts for Coefficient of Variation with Measurement Errors
- Goodness-of-Fit Tests for Component Lifetimes Distribution Based on System Failure Data with Known Signature
- Methodology of Using Empirical Distributions to Solve Business Optimization Problems
Machine Learning Applications
- Deep Learning-Based Scene Understanding Model for Assistive Systems Related to Alzheimer’s Patients

Applications and Case Studies

Business and Economic Models
- Modeling the Performance of Capital Constrained Firms
- Integrating Sentiment Analysis in Recommender Systems
Image Processing and Natural Language Processing
- Feature Matching Technique Using Similarity Features Filtering for Image Alignment
- Extended Sentence Similarity Based on Word Relations for Document Summarization
Engineering and Manufacturing
- Developing Alert Levels for Aircraft Components
- Application of Machine Learning for Failure Prediction in Manufacturing Processes

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