عنوان
پدید آورنده
موضوع
رده
QA76.9.B45
QA76
.
9
.
B45
کتابخانه
محل استقرار
INTERNATIONAL STANDARD BOOK NUMBER
(Number (ISBN
9789811076411
(Number (ISBN
9811076413
Erroneous ISBN
9789811076404
Erroneous ISBN
9811076405
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Data science and big data analytics :
General Material Designation
[Book]
Other Title Information
ACM-WIR 2018 /
First Statement of Responsibility
Durgesh Kumar Mishra, Xin-She Yang, Aynur Unal, editors.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Singapore :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
2019.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource
SERIES
Series Title
Lecture notes on data engineering and communications technologies,
Volume Designation
volume 16
ISSN of Series
2367-4512 ;
GENERAL NOTES
Text of Note
Includes author index.
CONTENTS NOTE
Text of Note
Intro; Preface; Contents; About the Editors; Keynote Speakers; Analysis and Evaluation of Big Data Video Quality in Wireless Networks; Publishing Ethics and Author Services; Applying Machine Learning Techniques for Big Data Analytics; Outlier Detection in Big Data; Identification and Prevention of Internet Addiction in Youth; Android: Security Issues; Tweaking Big Data Analysis for Malicious Intents; Big Data and Web Mining; Big Data and Data Science Trends: Challenges and Opportunities
Text of Note
2.4 ICESat/GLAS Data Processing3 Study Area and Materials; 4 Methodology; 5 Description of Datasets; 5.1 Satellite Data; 5.2 Field Data; 6 Genetic Approach for Optimization of LiDAR Biomass Estimation; 7 Optimization Genetic Algorithm Using R Package; 7.1 Calculate of RMSE; 8 Results and Discussions; 8.1 Analysis of GLAS Derived Waveform Parameters; 8.2 Results from Genetic Algorithm; 8.3 Biomass Equation Generated; 9 Conclusions; References
Text of Note
3 Proposed Work3.1 Problem Identification; 3.2 Methodology; 4 Performance Analysis; 4.1 Implementation; 4.2 Result Comparisons; 5 Conclusion; References; Baron-Cohen Model Based Personality Classification Using Ensemble Learning; 1 Introduction; 2 Related Work; 3 Implementation; 3.1 Data Set Details; 3.2 Hypothesis; 3.3 Machine Learning; 3.4 K-Fold Validation (K = 10); 3.5 Ensemble Learning; 4 Results; 5 Conclusion; References; Investigation of MANET Routing Protocols via Quantitative Metrics; 1 Introduction; 2 Related Work; 3 Routing Protocols; 4 Simulation Table and Results
Text of Note
A Study of the Correlation Between Internet Addiction and Aggressive Behaviour Among the Namibian University Students1 Introduction; 2 Literature Review; 3 Methodology; 3.1 Study Design and Population; 3.2 Measures and Data Collection; 3.3 Data Analysis; 4 Results and Analysis; 4.1 Descriptive Statistics; 4.2 Correlations Between Variables; 5 Conclusion; References; Genetic Algorithm Approach for Optimization of Biomass Estimation at LiDAR; 1 Introduction; 2 Review of Literature; 2.1 Biomass Estimation; 2.2 Review of Global Forest Biomass Assessment; 2.3 Spaceborne LiDAR (ICESat/GLAS)
Text of Note
E-alive: An Integrated Platform Based on Machine Learning Techniques to Aware and Educate Common People with the Current Statistics of Maternal and Child Health Care1 Introduction; 2 Motivation; 3 Preliminaries; 3.1 Maternal and Child Health Care Parameters; 3.2 Government Schemes; 3.3 Techniques of Data Mining; 4 System Implementation; 5 Results and Discussions; 6 Conclusion and Future Scope; References; An Effective TCP's Congestion Control Approach for Cross-Layer Design in MANET; 1 Introduction; 1.1 Mobile Ad Hoc Network; 1.2 Congestion Control; 1.3 Cross-Layer Design; 2 Literature Survey
0
8
8
8
8
SUMMARY OR ABSTRACT
Text of Note
This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
Springer Nature
Stock Number
com.springer.onix.9789811076411
OTHER EDITION IN ANOTHER MEDIUM
Title
Data science and big data analytics.
International Standard Book Number
9789811076404
PARALLEL TITLE PROPER
Parallel Title
ACM-WIR 2019
TOPICAL NAME USED AS SUBJECT
Big data, Congresses.
Data mining, Congresses.
Machine learning, Congresses.
Big data.
COMPUTERS-- Database-- General.
Data mining.
Machine learning.
(SUBJECT CATEGORY (Provisional
COM-- 021000
DEWEY DECIMAL CLASSIFICATION
Number
005
.
7
Edition
23
LIBRARY OF CONGRESS CLASSIFICATION
Class number
QA76
.
9
.
B45
PERSONAL NAME - ALTERNATIVE RESPONSIBILITY
Mishra, Durgesh Kumar
Unal, Aynur
Yang, Xin-She
CORPORATE BODY NAME - PRIMARY RESPONSIBILITY
ACM-WIR (Workshop)(2018 :, Indore, India)
ORIGINATING SOURCE
Date of Transaction
20200823222017.0
Cataloguing Rules (Descriptive Conventions))
pn
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب [Book]
Y
