Deep Learning And Missing Data In Engineering Systems
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Deep Learning And Missing Data In Engineering Systems
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Author : Collins Achepsah Leke
language : en
Publisher: Springer
Release Date : 2018-12-13
Deep Learning And Missing Data In Engineering Systems written by Collins Achepsah Leke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-13 with Technology & Engineering categories.
Deep Learning and Missing Data in Engineering Systems uses deep learning and swarm intelligence methods to cover missing data estimation in engineering systems. The missing data estimation processes proposed in the book can be applied in image recognition and reconstruction. To facilitate the imputation of missing data, several artificial intelligence approaches are presented, including: deep autoencoder neural networks; deep denoising autoencoder networks; the bat algorithm; the cuckoo search algorithm; and the firefly algorithm. The hybrid models proposed are used to estimate the missing data in high-dimensional data settings more accurately. Swarm intelligence algorithms are applied to address critical questions such as model selection and model parameter estimation. The authors address feature extraction for the purpose of reconstructing the input data from reduced dimensions by the use of deep autoencoder neural networks. They illustrate new models diagrammatically, report their findings in tables, so as to put their methods on a sound statistical basis. The methods proposed speed up the process of data estimation while preserving known features of the data matrix. This book is a valuable source of information for researchers and practitioners in data science. Advanced undergraduate and postgraduate students studying topics in computational intelligence and big data, can also use the book as a reference for identifying and introducing new research thrusts in missing data estimation.
Computational Intelligence For Missing Data Imputation Estimation And Management Knowledge Optimization Techniques
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Author : Marwala, Tshilidzi
language : en
Publisher: IGI Global
Release Date : 2009-04-30
Computational Intelligence For Missing Data Imputation Estimation And Management Knowledge Optimization Techniques written by Marwala, Tshilidzi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-30 with Computers categories.
"This book is for those who use data analysis to build decision support systems, particularly engineers, scientists and statisticians"--Provided by publisher.
Data Analytics In System Engineering
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Author : Radek Silhavy
language : en
Publisher: Springer Nature
Release Date :
Data Analytics In System Engineering written by Radek Silhavy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Machine Learning And Knowledge Discovery For Engineering Systems Health Management
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Author : Ashok N. Srivastava
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Machine Learning And Knowledge Discovery For Engineering Systems Health Management written by Ashok N. Srivastava and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Computers categories.
This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.
Handbook Of Machine Learning Volume 2 Optimization And Decision Making
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Author : Tshilidzi Marwala
language : en
Publisher: World Scientific
Release Date : 2019-11-21
Handbook Of Machine Learning Volume 2 Optimization And Decision Making written by Tshilidzi Marwala and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-21 with Computers categories.
Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.
Artificial Intelligence Game Theory And Mechanism Design In Politics
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Author : Tshilidzi Marwala
language : en
Publisher: Springer Nature
Release Date : 2023-08-04
Artificial Intelligence Game Theory And Mechanism Design In Politics written by Tshilidzi Marwala and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-04 with Political Science categories.
This book explores how AI and mechanism design can provide a new framework for international politics. The international political system is all manners in which countries, governments and people relate. Mechanism design in international politics relates to identifying rules that define relationships between people and countries that achieve a particular outcome, e.g., peace or more trade or democracy or economic development. Artificial intelligence is technique of making machines intelligent. This book explores mechanism design and artificial intelligence in international politics and applies these technologies to politics, economy and society. This book will be of interest to scholars of international relations, politics, sustainable development, and artificial intelligence.
Artificial Intelligence Methods In The Environmental Sciences
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Author : Sue Ellen Haupt
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-11-28
Artificial Intelligence Methods In The Environmental Sciences written by Sue Ellen Haupt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-28 with Science categories.
How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Feature Engineering Made Easy
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Author : Sinan Ozdemir
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-22
Feature Engineering Made Easy written by Sinan Ozdemir and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-22 with Computers categories.
A perfect guide to speed up the predicting power of machine learning algorithms Key Features Design, discover, and create dynamic, efficient features for your machine learning application Understand your data in-depth and derive astonishing data insights with the help of this Guide Grasp powerful feature-engineering techniques and build machine learning systems Book Description Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization. What you will learn Identify and leverage different feature types Clean features in data to improve predictive power Understand why and how to perform feature selection, and model error analysis Leverage domain knowledge to construct new features Deliver features based on mathematical insights Use machine-learning algorithms to construct features Master feature engineering and optimization Harness feature engineering for real world applications through a structured case study Who this book is for If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python scripting would be enough to get started with this book.
Emerging Research In Data Engineering Systems And Computer Communications
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Author : P. Venkata Krishna
language : en
Publisher: Springer Nature
Release Date : 2020-02-10
Emerging Research In Data Engineering Systems And Computer Communications written by P. Venkata Krishna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-10 with Computers categories.
This book gathers selected papers presented at the 2nd International Conference on Computing, Communications and Data Engineering, held at Sri Padmavati Mahila Visvavidyalayam, Tirupati, India from 1 to 2 Feb 2019. Chiefly discussing major issues and challenges in data engineering systems and computer communications, the topics covered include wireless systems and IoT, machine learning, optimization, control, statistics, and social computing.
Computational Sciences And Artificial Intelligence In Industry
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Author : Tero Tuovinen
language : en
Publisher: Springer Nature
Release Date : 2021-08-19
Computational Sciences And Artificial Intelligence In Industry written by Tero Tuovinen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-19 with Technology & Engineering categories.
This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors.