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Non intrusive Load Monitoring

introduction to related basic principles, while also proposing improvements. As the basis of demand-side energy management, the non-intrusive load;

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Non intrusive Load Monitoring

introduction to related basic principles, while also proposing improvements. As the basis of demand-side energy management, the non-intrusive load;

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Machine Learning Approaches to Non-Intrusive Load Monitoring

, Non-Intrusive Load Monitoring (NILM), the subject of this book, represents one of the hottest topics in Smart Grid applications. NILM refers;

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Machine Learning Systems

of failure and changes in load. But machine learning systems are different than other applications when it comes to testing, building, deploying, and;

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Condition Monitoring with Vibration Signals

presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance.A;

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Grammar Based Feature Generation for Time Series Prediction

. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction;

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Machine Learning for Cyber Physical Systems

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers;

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Machine Learning for Cyber Physical Systems

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers;

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Condition Monitoring and Faults Diagnosis of Induction Motors

electrical signature analysis. It aims to present a new non-invasive and non-intrusive condition monitoring system, which has the capability to;

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Financial Signal Processing and Machine Learning

processing and machine learning as key approaches to quantitative finance. * Offers advanced mathematical tools for high-dimensional portfolio;

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Machine Learning for Cyber Physical Systems

This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains;

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Infrastructure Monitoring with Spaceborne SAR Sensors

processing chain, and brings innovative technical aspects relative to conventional approaches. The book is intended primarily for professionals and;

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Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify;

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Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify;

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Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches

-nearest neighbours and unsupervised deep learning approaches - to develop more sophisticated and efficient monitoring techniques. Finally;

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Structural Health Monitoring and Engineering Structures

learning, deep learning, Artificial intelligent and non-destructive evaluation. It will be a reference for professionals and students in the areas;

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Machine Learning

, neurologists and health care practitioners. Provides a non-technical introduction to machine learning and applications to brain disorders;

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Towards Adaptive Spoken Dialog Systems

negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions;

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Machine Vision Inspection Systems

learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT;

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Big Data Application in Power Systems

, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data;

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Human-Computer interaction

about real-world applications of HCI techniques, non-intrusive physiological monitoring for affective sensing of computer users, modeling human;

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Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel;

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Machine Learning with Spark -

powerful tools to load, analyze, clean, and transform your data Who This Book Is For If you have a basic knowledge of machine learning and;

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Machine Learning Engineering with MLflow

MLflow in non-Python-based languages such as R and Java, along with covering approaches to extend MLflow with Plugins. By the end of this;

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Structural Health Monitoring

faculty working in SHM. Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem;

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Evolutionary Learning

Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non;

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Perioperative Monitoring, An Issue of Anesthesiology Clinics

to: Clinician monitoring, Ventilation monitoring, Measurement of pulmonary mechanics, Hemodynamic monitoring, Tissue perfusion monitoring;

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