Near Real Time Risk Assessment Using Hidden Markov Models
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Author | : Prashant Johri |
Publisher | : Springer Nature |
Total Pages | : 404 |
Release | : 2020-05-04 |
Genre | : Technology & Engineering |
ISBN | : 9811533571 |
This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
Author | : Walter Zucchini |
Publisher | : CRC Press |
Total Pages | : 370 |
Release | : 2017-12-19 |
Genre | : Mathematics |
ISBN | : 1482253844 |
Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data
Author | : Ali Emrouznejad |
Publisher | : Springer |
Total Pages | : 492 |
Release | : 2016-05-26 |
Genre | : Technology & Engineering |
ISBN | : 3319302655 |
The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.
Author | : Jemal H. Abawajy |
Publisher | : Springer Nature |
Total Pages | : 1040 |
Release | : 2023-04-07 |
Genre | : Computers |
ISBN | : 3031290976 |
This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.
Author | : Giampiero Mastinu |
Publisher | : Springer Nature |
Total Pages | : 1016 |
Release | : |
Genre | : |
ISBN | : 3031703928 |
Author | : MIT Critical Data |
Publisher | : Springer |
Total Pages | : 435 |
Release | : 2016-09-09 |
Genre | : Medical |
ISBN | : 3319437429 |
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
Author | : Andrew B. Lawson |
Publisher | : Wiley |
Total Pages | : 0 |
Release | : 1999-07-09 |
Genre | : Mathematics |
ISBN | : 9780471986348 |
Offers an in-depth report on advanced statistical tools for public health disease surveillance, which is the result of a prestigious World Health Organisation (WHO) and EU Biomed programme initiative. Traditionally, the role of public health disease surveillance has been to identify and evaluate morbidity and mortality but increasingly, more sophisticated methods are being applied as the authorities extend their studies to include control and prevention of disease. This book brings together leading experts to discuss complex methodologies for the statistical evaluation of disease mapping and risk assessment. It includes a broad variety of statistical techniques and where appropriate, examples are included on topical issues such as the analysis of putative health hazards. For easy reference the text is presented in five distinct sections, each with an introductory review: * Disease Mapping * Clustering of Disesase * Ecological Analysis * Risk Assessment for Putative Sources of Hazard * Public Health Applications and Case Studies Representative of the most pertinent issues within disease surveillance and mapping, this book will provide an accessible overview for statisticians and epidemiologists.
Author | : Diego Galar |
Publisher | : CRC Press |
Total Pages | : 491 |
Release | : 2021-12-27 |
Genre | : Technology & Engineering |
ISBN | : 1000518264 |
Maintenance combines various methods, tools, and techniques in a bid to reduce maintenance costs while increasing the reliability, availability, and security of equipment. Condition-based maintenance (CBM) is one such method, and prognostics forms a key element of a CBM program based on mathematical models for predicting remaining useful life (RUL). Prognostics and Remaining Useful Life (RUL) Estimation: Predicting with Confidence compares the techniques and models used to estimate the RUL of different assets, including a review of the relevant literature on prognostic techniques and their use in the industrial field. This book describes different approaches and prognosis methods for different assets backed up by appropriate case studies. FEATURES Presents a compendium of RUL estimation methods and technologies used in predictive maintenance Describes different approaches and prognosis methods for different assets Includes a comprehensive compilation of methods from model-based and data-driven to hybrid Discusses the benchmarking of RUL estimation methods according to accuracy and uncertainty, depending on the target application, the type of asset, and the forecast performance expected Contains a toolset of methods and a way of deployment aimed at a versatile audience This book is aimed at professionals, senior undergraduates, and graduate students in all interdisciplinary engineering streams that focus on prognosis and maintenance.
Author | : Mark Gales |
Publisher | : Now Publishers Inc |
Total Pages | : 125 |
Release | : 2008 |
Genre | : Automatic speech recognition |
ISBN | : 1601981201 |
The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
Author | : Martinetti, Alberto |
Publisher | : IGI Global |
Total Pages | : 321 |
Release | : 2020-06-26 |
Genre | : Technology & Engineering |
ISBN | : 1799839052 |
To plan, build, monitor, maintain, and dispose of products and assets properly, maintenance and safety requirements must be implemented and followed. A lack of maintenance and safety protocols leads to accidents and environmental disasters as well as unexpected downtime that costs businesses money and time. With the arrival of the Fourth Industrial Revolution and evolving technological tools, it is imperative that safety and maintenance practices be reexamined. Applications and Challenges of Maintenance and Safety Engineering in Industry 4.0 is a collection of innovative research that addresses safety and design for maintenance and reducing the factors that influence and degrade human performance and that provides technological advancements and emergent technologies that reduce the dependence on operator capabilities. Highlighting a wide range of topics including management analytics, internet of things (IoT), and maintenance, this book is ideally designed for engineers, software designers, technology developers, managers, safety officials, researchers, academicians, and students.