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Machine learning and big data analyt...
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Darwish, Ashraf.
Machine learning and big data analytics paradigmsanalysis, applications and challenges /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Machine learning and big data analytics paradigmsedited by Aboul Ella Hassanien, Ashraf Darwish.
其他題名:
analysis, applications and challenges /
其他作者:
Hassanien, Aboul Ella.
出版者:
Cham :Springer International Publishing :2021.
面頁冊數:
xi, 648 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Machine learning.
電子資源:
https://doi.org/10.1007/978-3-030-59338-4
ISBN:
9783030593384$q(electronic bk.)
Machine learning and big data analytics paradigmsanalysis, applications and challenges /
Machine learning and big data analytics paradigms
analysis, applications and challenges /[electronic resource] :edited by Aboul Ella Hassanien, Ashraf Darwish. - Cham :Springer International Publishing :2021. - xi, 648 p. :ill., digital ;24 cm. - Studies in big data,v.772197-6503 ;. - Studies in big data ;v.1..
Rough Sets and Rule Induction from Indiscernibility Relations Based on Possible World Semantics in Incomplete Information Systems with Continuous Domains -- Big Data Analytics and Preprocessing -- Artificial Intelligence-based Plant Diseases Classification -- Artificial Intelligence in Potato Leaf Disease Classification: A Deep Learning Approach -- Granules-Based Rough Set Theory for Circuit Breaker Fault Diagnosis -- SQL Injection Attacks Detection and Prevention based on Neuro-Fuzzy Technique -- Convolutional Neural Network with Batch Normalization for Classification of Endoscopic Gastrointestinal Diseases -- A Chaotic Search-Enhanced Genetic Algorithm for Bilevel Programming Problems -- Bio-Inspired Machine Learning Mechanism for Detecting Malicious URL through Passive DNS in Big Data Platform -- Target Analytical: A Text Analytics Framework for Ranking Therapeutic Molecules in the Bibliome -- Earthquakes and Thermal Anomalies in a Remote Sensing Perspective -- Literature Review with Study and Analysis of the Quality Challenges of Recommendation Techniques and their Application in Movie Ratings -- Predicting Student Retention Among a Homogeneous Population using Data Mining -- An Approach for Textual Based Clustering Using Word Embedding -- A Survey on Speckle Noise Reduction in SAR Images -- Comparative Analysis of Different Approaches to Human Activity Recognition based on Accelerometer Signals -- Soil Morphology based on Deep Learning, Polynomial Learning and Gabor Teager-Kaiser Energy Operators -- Deep Layer Convolutional Neural Network (CNN) Architecture for Breast Cancer Classification Using Histopathological Images -- A survey on Deep Learning for Time-Series Forecasting -- Deep Learning for Taxonomic Classification of Biological Bacterial Sequences -- Particle Swarm Optimization and Grey Wolf Optimizer to Solve Continuous p-Median Location Problems -- Gene Ontology Analysis of Gene Expression Data Using Hybridized PSO Triclustering (HSPO-TriC) Model -- Experimental Studies of Variations Reduction in Chemometric Model Transfer for FT-NIR Miniaturized Sensors -- Smart Environments Concepts, Applications, and Challenges -- Synonym Multi-Keyword Search over Encrypted Data Using Hierarchical Bloom Filters Index -- Assessing the Performance of E-government Services through Multi-Criteria Analysis: The Case of Egypt -- IoTIwC: IoT Industrial Wireless Controller -- Applying Software Defined Network Concepts for Securing the Client data signals over the Optical Transport Network of Egypt -- Watermarking 3D printing Data Based on Coyote Optimization Algorithm -- A 3D Geolocation Analysis of an RF Emitter Source with Two RF Sensors Based on Time and Angle of Arrival.
This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
ISBN: 9783030593384$q(electronic bk.)
Standard No.: 10.1007/978-3-030-59338-4doiSubjects--Topical Terms:
188639
Machine learning.
LC Class. No.: Q325.5
Dewey Class. No.: 006.31
Machine learning and big data analytics paradigmsanalysis, applications and challenges /
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