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Computational Intelligence Applications in Business Intelligence and Big Data Analytics Vital Source e-bog
Vijayan Sugumaran
(2017)
Taylor & Francis
572,00 kr.
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Computational Intelligence Applications in Business Intelligence and Big Data Analytics
Vijayan Sugumaran, Arun Kumar Sangaiah og Arunkumar Thangavelu
(2017)
Sprog: Engelsk
Taylor & Francis Group
1.391,00 kr.
Print on demand. Leveringstid vil være ca 2-3 uger.
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: Taylor & Francis (Juni 2017)
- ISBN: 9781351720243
There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.
Licens varighed:
Bookshelf online: 5 år fra købsdato.
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Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: -1 sider kan printes ad gangen
Copy: højest -1 sider i alt kan kopieres (copy/paste)
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: -1 sider kan printes ad gangen
Copy: højest -1 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Hardback: 362 sider
- Udgiver: Taylor & Francis Group (Juni 2017)
- Forfattere: Vijayan Sugumaran, Arun Kumar Sangaiah og Arunkumar Thangavelu
- ISBN: 9781498761017
There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.
Editors Contributors Part I INTRODUCTION
1 Computational Intelligence Paradigms in Business Intelligence and Analytics Part II COMPUTAT IONAL INTELLIGENCE IN BUSINESS INTELLIGENCE AND ANALYTICS 2 Conditional Value at Risk-Based Portfolio Optimization Using Metaheuristic Approaches 3 Big Data Analysis and Application for Video Surveillance Systems 4 Trends in Mining Biological Big Data 5 Computational Challenges in Group Membership Prediction of Highly Imbalanced Big Data Sets Part III DATA ANALYTICS AND PREDICTION MODELS 6 A New Paradigm in Fraud Detection Modeling Using Predictive Models, Fuzzy Expert Systems, Social Network Analysis, and Unstructured Data 7 Speedy Data Analytics through Automatic Balancing of Big Data in MongoDB Sharded Clusters 8 Smart Metering as a Service Using Hadoop (SMAASH 9 Service-Oriented Architecture for Big Data and Business Intelligence Analytics in the Cloud Part IV A PPLICAT IONS OF COMPUTAT IONAL INTELLIGENCE 10 Rough Set and Neighborhood Systems in Big Data Analysis 11 An Investigation of Fuzzy Techniques in Clustering of Big Data 12 A Survey on Learning Models with Respect to Human Behavior Analysis for Large-Scale Surveillance Videos 13 Mining Unstructured Big Data for Competitive Intelligence and Business Intelligence
Index
1 Computational Intelligence Paradigms in Business Intelligence and Analytics Part II COMPUTAT IONAL INTELLIGENCE IN BUSINESS INTELLIGENCE AND ANALYTICS 2 Conditional Value at Risk-Based Portfolio Optimization Using Metaheuristic Approaches 3 Big Data Analysis and Application for Video Surveillance Systems 4 Trends in Mining Biological Big Data 5 Computational Challenges in Group Membership Prediction of Highly Imbalanced Big Data Sets Part III DATA ANALYTICS AND PREDICTION MODELS 6 A New Paradigm in Fraud Detection Modeling Using Predictive Models, Fuzzy Expert Systems, Social Network Analysis, and Unstructured Data 7 Speedy Data Analytics through Automatic Balancing of Big Data in MongoDB Sharded Clusters 8 Smart Metering as a Service Using Hadoop (SMAASH 9 Service-Oriented Architecture for Big Data and Business Intelligence Analytics in the Cloud Part IV A PPLICAT IONS OF COMPUTAT IONAL INTELLIGENCE 10 Rough Set and Neighborhood Systems in Big Data Analysis 11 An Investigation of Fuzzy Techniques in Clustering of Big Data 12 A Survey on Learning Models with Respect to Human Behavior Analysis for Large-Scale Surveillance Videos 13 Mining Unstructured Big Data for Competitive Intelligence and Business Intelligence
Index
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