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Applications in reliability and stat...

Pham, Hoang.

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Applications in reliability and statistical computing

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applications in reliability and statistical computing/ edited by Hoang Pham.
other author:	Pham, Hoang.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xiii, 302 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	1.Forecasting The Long-Term Growth of S&P 500 Index -- 2.Smart Maintenance and Human Factor Modeling for Aircraft Safety -- 3.Feedback-based algorithm for negotiating human preferences and making risk assessment decisions -- 4.Joining Aspect Detection and Opinion Target Expression based on Multi-Deep Learning Models -- 5.Voting Systems with Supervising Mechanisms -- 6.Assessing the Severity of COVID-19 in the United States -- 7.Promoting expert knowledge for comprehensive human risk management in industrial environments -- 8.Data Quality Assessment for ML Decision-Making -- 9.From Holistic Health to Holistic Reliability - Toward an Integration of Classical Reliability with Modern Big-data Based Health Monitoring -- 10.On the Aspects of Vitamin D and COVID-19 Infections and Modeling Time-delay Body's Immune System With Time-dependent Effects of Vitamin D and Probiotic -- 11.A Staff Scheduling Problem of Customers with Reservations in Consideration With Expected Wait Time of a Customer Without Reservation -- 12.Decision Support System for Ranking of Software Reliability Growth Models -- 13.Human Pose Estimation using Artificial Intelligence -- 14.Neural Network Modeling and What-if Scenarios: Applications for Market Development Forecasting -- 15.Mental Health Studies: A Review.
Contained By:	Springer Nature eBook
Subject:	Computer systems - Reliability. -
Online resource:	https://doi.org/10.1007/978-3-031-21232-1
ISBN:	9783031212321

Applications in reliability and statistical computing
Applications in reliability and statistical computing[electronic resource] /edited by Hoang Pham. - Cham :Springer International Publishing :2023. - xiii, 302 p. :ill. (some col.), digital ;24 cm. - Springer series in reliability engineering,2196-999X. - Springer series in reliability engineering..

1.Forecasting The Long-Term Growth of S&P 500 Index -- 2.Smart Maintenance and Human Factor Modeling for Aircraft Safety -- 3.Feedback-based algorithm for negotiating human preferences and making risk assessment decisions -- 4.Joining Aspect Detection and Opinion Target Expression based on Multi-Deep Learning Models -- 5.Voting Systems with Supervising Mechanisms -- 6.Assessing the Severity of COVID-19 in the United States -- 7.Promoting expert knowledge for comprehensive human risk management in industrial environments -- 8.Data Quality Assessment for ML Decision-Making -- 9.From Holistic Health to Holistic Reliability - Toward an Integration of Classical Reliability with Modern Big-data Based Health Monitoring -- 10.On the Aspects of Vitamin D and COVID-19 Infections and Modeling Time-delay Body's Immune System With Time-dependent Effects of Vitamin D and Probiotic -- 11.A Staff Scheduling Problem of Customers with Reservations in Consideration With Expected Wait Time of a Customer Without Reservation -- 12.Decision Support System for Ranking of Software Reliability Growth Models -- 13.Human Pose Estimation using Artificial Intelligence -- 14.Neural Network Modeling and What-if Scenarios: Applications for Market Development Forecasting -- 15.Mental Health Studies: A Review.

This book discusses practical applications of reliability and statistical methods and techniques in various disciplines, using machine learning, artificial intelligence, optimization, and other computation methods. Bringing together research from international experts, each chapter aims to cover both methods and practical aspects on reliability or statistical computations with emphasis on applications. 5G and IoT are set to generate an estimated 1 billion terabytes of data by 2025 and companies continue to search for new techniques and tools that can help them practice data collection effectively in promoting their business. This book explores the era of big data through reliability and statistical computing, showcasing how almost all applications in our daily life have experienced a dramatic shift in the past two decades to a truly global industry. Including numerous illustrations and worked examples, the book is of interest to researchers, practicing engineers, and postgraduate students in the fields of reliability engineering, statistical computing, and machine learning.

ISBN: 9783031212321

Standard No.: 10.1007/978-3-031-21232-1doiSubjects--Topical Terms:

805512
Computer systems
--Reliability.

LC Class. No.: QA76.76.R44 / A67 2023

Dewey Class. No.: 004

Applications in reliability and statistical computing
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300 $a xiii, 302 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Springer series in reliability engineering, $x 2196-999X
505 0 $a 1.Forecasting The Long-Term Growth of S&P 500 Index -- 2.Smart Maintenance and Human Factor Modeling for Aircraft Safety -- 3.Feedback-based algorithm for negotiating human preferences and making risk assessment decisions -- 4.Joining Aspect Detection and Opinion Target Expression based on Multi-Deep Learning Models -- 5.Voting Systems with Supervising Mechanisms -- 6.Assessing the Severity of COVID-19 in the United States -- 7.Promoting expert knowledge for comprehensive human risk management in industrial environments -- 8.Data Quality Assessment for ML Decision-Making -- 9.From Holistic Health to Holistic Reliability - Toward an Integration of Classical Reliability with Modern Big-data Based Health Monitoring -- 10.On the Aspects of Vitamin D and COVID-19 Infections and Modeling Time-delay Body's Immune System With Time-dependent Effects of Vitamin D and Probiotic -- 11.A Staff Scheduling Problem of Customers with Reservations in Consideration With Expected Wait Time of a Customer Without Reservation -- 12.Decision Support System for Ranking of Software Reliability Growth Models -- 13.Human Pose Estimation using Artificial Intelligence -- 14.Neural Network Modeling and What-if Scenarios: Applications for Market Development Forecasting -- 15.Mental Health Studies: A Review.
520 $a This book discusses practical applications of reliability and statistical methods and techniques in various disciplines, using machine learning, artificial intelligence, optimization, and other computation methods. Bringing together research from international experts, each chapter aims to cover both methods and practical aspects on reliability or statistical computations with emphasis on applications. 5G and IoT are set to generate an estimated 1 billion terabytes of data by 2025 and companies continue to search for new techniques and tools that can help them practice data collection effectively in promoting their business. This book explores the era of big data through reliability and statistical computing, showcasing how almost all applications in our daily life have experienced a dramatic shift in the past two decades to a truly global industry. Including numerous illustrations and worked examples, the book is of interest to researchers, practicing engineers, and postgraduate students in the fields of reliability engineering, statistical computing, and machine learning.
650 0 $a Computer systems $x Reliability. $3 805512
650 0 $a Reliability (Engineering) $x Data processing. $3 884377
650 0 $a Mathematical statistics $x Data processing. $3 532521
650 1 4 $a Industrial Management. $3 3537892
650 2 4 $a Hardware Performance and Reliability. $3 3538539
650 2 4 $a Operations Research and Decision Theory. $3 3591727
650 2 4 $a Mathematical Modeling and Industrial Mathematics. $3 891089
700 1 $a Pham, Hoang. $3 784005
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Springer series in reliability engineering. $3 1565557
856 4 0 $u https://doi.org/10.1007/978-3-031-21232-1
950 $a Engineering (SpringerNature-11647)