Practical Applications Of Data Processing Algorithms And Modeling

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Practical Applications of Data Processing, Algorithms, and Modeling

Whig, Pawan,Sharma, Sachinn,Sharma, Seema,Jain, Anupriya,Yathiraju, Nikhitha
Practical Applications of Data Processing Algorithms and Modeling Book PDF

Author : Whig, Pawan,Sharma, Sachinn,Sharma, Seema,Jain, Anupriya,Yathiraju, Nikhitha
Publisher : IGI Global
Page : 334 pages
File Size : 40,5 Mb
Release : 2024-04-29
Category : Computers
ISBN : 9798369329108

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Practical Applications of Data Processing, Algorithms, and Modeling by Whig, Pawan,Sharma, Sachinn,Sharma, Seema,Jain, Anupriya,Yathiraju, Nikhitha Pdf

In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.

Applications of Big Data Analytics

Mohammed M. Alani,Hissam Tawfik,Mohammed Saeed,Obinna Anya
Applications of Big Data Analytics Book PDF

Author : Mohammed M. Alani,Hissam Tawfik,Mohammed Saeed,Obinna Anya
Publisher : Springer
Page : 214 pages
File Size : 42,8 Mb
Release : 2018-07-23
Category : Computers
ISBN : 9783319764726

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Applications of Big Data Analytics by Mohammed M. Alani,Hissam Tawfik,Mohammed Saeed,Obinna Anya Pdf

This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery. Topics and features: Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects. Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.

Radar Data Processing With Applications

He You,Xiu Jianjuan,Guan Xin
Radar Data Processing With Applications Book PDF

Author : He You,Xiu Jianjuan,Guan Xin
Publisher : John Wiley & Sons
Page : 560 pages
File Size : 40,7 Mb
Release : 2016-08-01
Category : Technology & Engineering
ISBN : 9781118956892

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Radar Data Processing With Applications by He You,Xiu Jianjuan,Guan Xin Pdf

A systematic introduction to the theory, development and latest research results of radar data processing technology • Presents both classical theory and development methods of radar data processing • Provides state-of-the-art research results, including data processing for modern style radars, and tracking performance evaluation theory • Includes coverage of performance evaluation, registration algorithm for Radar network, data processing of passive radar, pulse Doppler radar, and phased array radar • Has applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command

Risk Modeling

Terisa Roberts,Stephen J. Tonna
Risk Modeling Book PDF

Author : Terisa Roberts,Stephen J. Tonna
Publisher : John Wiley & Sons
Page : 214 pages
File Size : 47,5 Mb
Release : 2022-09-20
Category : Business & Economics
ISBN : 9781119824947

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Risk Modeling by Terisa Roberts,Stephen J. Tonna Pdf

A wide-ranging overview of the use of machine learning and AI techniques in financial risk management, including practical advice for implementation Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning introduces readers to the use of innovative AI technologies for forecasting and evaluating financial risks. Providing up-to-date coverage of the practical application of current modelling techniques in risk management, this real-world guide also explores new opportunities and challenges associated with implementing machine learning and artificial intelligence (AI) into the risk management process. Authors Terisa Roberts and Stephen Tonna provide readers with a clear understanding about the strengths and weaknesses of machine learning and AI while explaining how they can be applied to both everyday risk management problems and to evaluate the financial impact of extreme events such as global pandemics and changes in climate. Throughout the text, the authors clarify misconceptions about the use of machine learning and AI techniques using clear explanations while offering step-by-step advice for implementing the technologies into an organization's risk management model governance framework. This authoritative volume: Highlights the use of machine learning and AI in identifying procedures for avoiding or minimizing financial risk Discusses practical tools for assessing bias and interpretability of resultant models developed with machine learning algorithms and techniques Covers the basic principles and nuances of feature engineering and common machine learning algorithms Illustrates how risk modeling is incorporating machine learning and AI techniques to rapidly consume complex data and address current gaps in the end-to-end modelling lifecycle Explains how proprietary software and open-source languages can be combined to deliver the best of both worlds: for risk models and risk practitioners Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning is an invaluable guide for CEOs, CROs, CFOs, risk managers, business managers, and other professionals working in risk management.

Big Data

Kuan-Ching Li,Hai Jiang,Laurence T. Yang,Alfredo Cuzzocrea
Big Data Book PDF

Author : Kuan-Ching Li,Hai Jiang,Laurence T. Yang,Alfredo Cuzzocrea
Publisher : Chapman and Hall/CRC
Page : 0 pages
File Size : 48,5 Mb
Release : 2015-02-23
Category : Computers
ISBN : 1482240556

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Big Data by Kuan-Ching Li,Hai Jiang,Laurence T. Yang,Alfredo Cuzzocrea Pdf

As today’s organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages. Presenting the contributions of leading experts in their respective fields, Big Data: Algorithms, Analytics, and Applications bridges the gap between the vastness of Big Data and the appropriate computational methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data, better analytical strategies to digest data, and representative applications in diverse fields, such as medicine, science, and engineering. The book is organized into five main sections: Big Data Management—considers the research issues related to the management of Big Data, including indexing and scalability aspects Big Data Processing—addresses the problem of processing Big Data across a wide range of resource-intensive computational settings Big Data Stream Techniques and Algorithms—explores research issues regarding the management and mining of Big Data in streaming environments Big Data Privacy—focuses on models, techniques, and algorithms for preserving Big Data privacy Big Data Applications—illustrates practical applications of Big Data across several domains, including finance, multimedia tools, biometrics, and satellite Big Data processing Overall, the book reports on state-of-the-art studies and achievements in algorithms, analytics, and applications of Big Data. It provides readers with the basis for further efforts in this challenging scientific field that will play a leading role in next-generation database, data warehousing, data mining, and cloud computing research. It also explores related applications in diverse sectors, covering technologies for media/data communication, elastic media/data storage, cross-network media/data fusion, and SaaS.

Knowledge Graphs and Big Data Processing

Valentina Janev,Damien Graux,Hajira Jabeen,Emanuel Sallinger
Knowledge Graphs and Big Data Processing Book PDF

Author : Valentina Janev,Damien Graux,Hajira Jabeen,Emanuel Sallinger
Publisher : Springer Nature
Page : 212 pages
File Size : 42,9 Mb
Release : 2020-07-15
Category : Computers
ISBN : 9783030531997

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Knowledge Graphs and Big Data Processing by Valentina Janev,Damien Graux,Hajira Jabeen,Emanuel Sallinger Pdf

This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.

Time Series Analysis, Modeling and Applications

Witold Pedrycz,Shyi-Ming Chen
Time Series Analysis Modeling and Applications Book PDF

Author : Witold Pedrycz,Shyi-Ming Chen
Publisher : Springer Science & Business Media
Page : 398 pages
File Size : 51,7 Mb
Release : 2012-11-29
Category : Technology & Engineering
ISBN : 9783642334399

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Time Series Analysis, Modeling and Applications by Witold Pedrycz,Shyi-Ming Chen Pdf

Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological and algorithmic approaches and case studies. This volume is aimed at a broad audience of researchers and practitioners engaged in various branches of operations research, management, social sciences, engineering, and economics. Owing to the nature of the material being covered and a way it has been arranged, it establishes a comprehensive and timely picture of the ongoing pursuits in the area and fosters further developments.

2020 International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems

Chuanchao Huang,Yu-Wei Chan,Neil Yen
2020 International Conference on Data Processing Techniques and Applications for Cyber Physical Systems Book PDF

Author : Chuanchao Huang,Yu-Wei Chan,Neil Yen
Publisher : Springer Nature
Page : 1669 pages
File Size : 45,5 Mb
Release : 2021-06-01
Category : Technology & Engineering
ISBN : 9789811617263

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2020 International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems by Chuanchao Huang,Yu-Wei Chan,Neil Yen Pdf

This book covers cutting-edge and advanced research on data processing techniques and applications for cyber-physical systems, gathering the proceedings of the International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2020), held in Laibin City, Guangxi Province, China, on December 11–12, 2020. It examines a wide range of topics, including distributed processing for sensor data in CPS networks; approximate reasoning and pattern recognition for CPS networks; data platforms for efficient integration with CPS networks; machine learning algorithms for CPS networks; and data security and privacy in CPS networks. Outlining promising future research directions, the book offers a valuable resource for students, researchers, and professionals alike, while also providing a useful reference guide for newcomers to the field.

Intelligent Data Engineering and Automated Learning – IDEAL 2015

Konrad Jackowski,Robert Burduk,Krzysztof Walkowiak,Michal Wozniak,Hujun Yin
Intelligent Data Engineering and Automated Learning IDEAL 2015 Book PDF

Author : Konrad Jackowski,Robert Burduk,Krzysztof Walkowiak,Michal Wozniak,Hujun Yin
Publisher : Springer
Page : 560 pages
File Size : 49,5 Mb
Release : 2015-10-13
Category : Computers
ISBN : 9783319248349

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Intelligent Data Engineering and Automated Learning – IDEAL 2015 by Konrad Jackowski,Robert Burduk,Krzysztof Walkowiak,Michal Wozniak,Hujun Yin Pdf

This book constitutes the refereed proceedings of the 16th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2015, held in Wroclaw, Poland, in October 2015. The 64 revised full papers presented were carefully reviewed and selected from 127 submissions. These papers provided a valuable collection of recent research outcomes in data engineering and automated learning, from methodologies, frameworks, and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modeling, swarm intelligent, multi-objective optimization, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, IDEAL 2015 also featured a number of special sessions on several emerging topics such as computational intelligence for optimization of communication networks, discovering knowledge from data, simulation-driven DES-like modeling and performance evaluation, and intelligent applications in real-world problems.

Advances in Artificial Intelligence and Security

Xingming Sun,Xiaorui Zhang,Zhihua Xia,Elisa Bertino
Advances in Artificial Intelligence and Security Book PDF

Author : Xingming Sun,Xiaorui Zhang,Zhihua Xia,Elisa Bertino
Publisher : Springer Nature
Page : 730 pages
File Size : 47,8 Mb
Release : 2022-07-08
Category : Computers
ISBN : 9783031067679

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Advances in Artificial Intelligence and Security by Xingming Sun,Xiaorui Zhang,Zhihua Xia,Elisa Bertino Pdf

The 3-volume set CCIS 1586, CCIS 1587 and CCIS 1588 constitutes the refereed proceedings of the 8th International Conference on Artificial Intelligence and Security, ICAIS 2022, which was held in Qinghai, China, in July 2022. The total of 115 full papers and 53 short papers presented in this 3-volume proceedings was carefully reviewed and selected from 1124 submissions. The papers were organized in topical sections as follows: Part I: artificial intelligence; Part II: artificial intelligence; big data; cloud computing and security; multimedia forensics; Part III: encryption and cybersecurity; information hiding; IoT security.

Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion

Christian Servin,Vladik Kreinovich
Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure related Data Processing and Data Fusion Book PDF

Author : Christian Servin,Vladik Kreinovich
Publisher : Springer
Page : 112 pages
File Size : 41,6 Mb
Release : 2014-11-20
Category : Technology & Engineering
ISBN : 9783319126289

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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion by Christian Servin,Vladik Kreinovich Pdf

On various examples ranging from geosciences to environmental sciences, this book explains how to generate an adequate description of uncertainty, how to justify semiheuristic algorithms for processing uncertainty, and how to make these algorithms more computationally efficient. It explains in what sense the existing approach to uncertainty as a combination of random and systematic components is only an approximation, presents a more adequate three-component model with an additional periodic error component, and explains how uncertainty propagation techniques can be extended to this model. The book provides a justification for a practically efficient heuristic technique (based on fuzzy decision-making). It explains how the computational complexity of uncertainty processing can be reduced. The book also shows how to take into account that in real life, the information about uncertainty is often only partially known, and, on several practical examples, explains how to extract the missing information about uncertainty from the available data.

Deep Learning: Practical Neural Networks with Java

Yusuke Sugomori,Bostjan Kaluza,Fabio M. Soares,Alan M. F. Souza
Deep Learning Practical Neural Networks with Java Book PDF

Author : Yusuke Sugomori,Bostjan Kaluza,Fabio M. Soares,Alan M. F. Souza
Publisher : Packt Publishing Ltd
Page : 744 pages
File Size : 43,5 Mb
Release : 2017-06-08
Category : Computers
ISBN : 9781788471718

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Deep Learning: Practical Neural Networks with Java by Yusuke Sugomori,Bostjan Kaluza,Fabio M. Soares,Alan M. F. Souza Pdf

Build and run intelligent applications by leveraging key Java machine learning libraries About This Book Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications This step-by-step guide will help you solve real-world problems and links neural network theory to their application Who This Book Is For This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life. What You Will Learn Get a practical deep dive into machine learning and deep learning algorithms Explore neural networks using some of the most popular Deep Learning frameworks Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts, algorithms, and the toolbox for deep learning Select and split data sets into training, test, and validation, and explore validation strategies Apply the code generated in practical examples, including weather forecasting and pattern recognition In Detail Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work. The course provides you with highly practical content explaining deep learning with Java, from the following Packt books: Java Deep Learning Essentials Machine Learning in Java Neural Network Programming with Java, Second Edition Style and approach This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application

Practical Data Science with Hadoop and Spark

Ofer Mendelevitch,Casey Stella,Douglas Eadline
Practical Data Science with Hadoop and Spark Book PDF

Author : Ofer Mendelevitch,Casey Stella,Douglas Eadline
Publisher : Addison-Wesley Professional
Page : 463 pages
File Size : 46,5 Mb
Release : 2016-12-08
Category : Computers
ISBN : 9780134029726

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Practical Data Science with Hadoop and Spark by Ofer Mendelevitch,Casey Stella,Douglas Eadline Pdf

The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language

Practical Applications of Computational Intelligence Techniques

Lakhmi Jain,Philippe De Wilde
Practical Applications of Computational Intelligence Techniques Book PDF

Author : Lakhmi Jain,Philippe De Wilde
Publisher : Springer Science & Business Media
Page : 392 pages
File Size : 53,9 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9789401006781

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Practical Applications of Computational Intelligence Techniques by Lakhmi Jain,Philippe De Wilde Pdf

Computational intelligence paradigms have attracted the growing interest of researchers, scientists, engineers and application engineers in a number of everyday applications. These applications are not limited to any particular field and include engineering, business, banking and consumer electronics. Computational intelligence paradigms include artificial intelligence, artificial neural networks, fuzzy systems and evolutionary computing. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimisation applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge. Practical Applications of Computational Intelligence Techniques contains twelve chapters providing actual application of these techniques in the real world. Such examples include, but are not limited to, intelligent household appliances, aerial spray models, industrial applications and medical diagnostics and practice. This book will be useful to researchers, practicing engineers/scientists and students, who are interested in developing practical applications in a computational intelligence environment.

On the Move to Meaningful Internet Systems: OTM 2018 Workshops

Christophe Debruyne,Hervé Panetto,Wided Guédria,Peter Bollen,Ioana Ciuciu,Robert Meersman
On the Move to Meaningful Internet Systems OTM 2018 Workshops Book PDF

Author : Christophe Debruyne,Hervé Panetto,Wided Guédria,Peter Bollen,Ioana Ciuciu,Robert Meersman
Publisher : Springer
Page : 261 pages
File Size : 47,8 Mb
Release : 2019-02-06
Category : Computers
ISBN : 9783030116835

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On the Move to Meaningful Internet Systems: OTM 2018 Workshops by Christophe Debruyne,Hervé Panetto,Wided Guédria,Peter Bollen,Ioana Ciuciu,Robert Meersman Pdf

This volume constitutes the refereed proceedings of the Confederated International International Workshop on Enterprise Integration, Interoperability and Networking (EI2N ), Fact Based Modeling ( FBM), Industry Case Studies Program ( ICSP ), and International Workshop on Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society (Meta4eS), held as part of OTM 2018 in October 2018 in Valletta, Malta. As the three main conferences and the associated workshops all share the distributed aspects of modern computing systems, they experience the application pull created by the Internet and by the so-called Semantic Web, in particular developments of Big Data, increased importance of security issues, and the globalization of mobile-based technologies.