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Networks Data Mining And Artificial Intelligence


Networks Data Mining And Artificial Intelligence
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Networks Data Mining And Artificial Intelligence


Networks Data Mining And Artificial Intelligence
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Author : Dhruba K. Bhattacharyya
language : en
Publisher:
Release Date : 2006

Networks Data Mining And Artificial Intelligence written by Dhruba K. Bhattacharyya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.


Networks, Data Mining and Artificial Intelligence reflects current research in WSN, Data Clustering & Association Mining and emerging topics in AI. Various routing and security issues in WSN are dealt in Sections I and II. These two sections discuss Congestion control in wireless environment, signal interference between WLAN & LR-WPAN and its avoidance and Quality of service routing in MANETs. Section III covers significant contributions on design of efficient clustering algorithms for categorical and mixed data types. This section includes an exhaustive survey on data clustering techniques. Section IV includes a probabilistic model for off-line handwritten Manipuri character recognition and a method for acquisition of morphological features of Assamese language. A soft computing technique for colour and texture discrimination for the tea industry is also discussed. This section also includes a method for fast computation of Legendre moments.



Data Mining With Neural Networks


Data Mining With Neural Networks
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Author : Joseph P. Bigus
language : en
Publisher: McGraw-Hill Companies
Release Date : 1996

Data Mining With Neural Networks written by Joseph P. Bigus and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Business & Economics categories.


readers will find concrete implementation strategies, reinforced with real-world business examples and a minimum of formulas, and case studies drawn from a broad range of industries. The book illustrates the popular data mining functions of classification, clustering, modeling, and time-series forecasting--through examples developed using the IBM Neural Network Utility.



Artificial Intelligence In Data Mining


Artificial Intelligence In Data Mining
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Author : D. Binu
language : en
Publisher: Academic Press
Release Date : 2021-02-17

Artificial Intelligence In Data Mining written by D. Binu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-17 with Science categories.


Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. - Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering - Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks - Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense



Data Mining With Computational Intelligence


Data Mining With Computational Intelligence
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Author : Lipo Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-08

Data Mining With Computational Intelligence written by Lipo Wang 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 2005-12-08 with Computers categories.


Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.



Advances In Knowledge Discovery And Data Mining


Advances In Knowledge Discovery And Data Mining
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Author : Hady W. Lauw
language : en
Publisher: Springer Nature
Release Date : 2020-05-08

Advances In Knowledge Discovery And Data Mining written by Hady W. Lauw and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Computers categories.


The two-volume set LNAI 12084 and 12085 constitutes the thoroughly refereed proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic. The 135 full papers presented were carefully reviewed and selected from 628 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: recommender systems; classification; clustering; mining social networks; representation learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.



Advances In Knowledge Discovery And Data Mining


Advances In Knowledge Discovery And Data Mining
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Author : Hady W. Lauw
language : en
Publisher: Springer Nature
Release Date : 2020-05-08

Advances In Knowledge Discovery And Data Mining written by Hady W. Lauw and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Computers categories.


The two-volume set LNAI 12084 and 12085 constitutes the thoroughly refereed proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic. The 135 full papers presented were carefully reviewed and selected from 628 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: recommender systems; classification; clustering; mining social networks; representation learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.



Data Mining And Machine Learning Applications


Data Mining And Machine Learning Applications
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Author : Rohit Raja
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-26

Data Mining And Machine Learning Applications written by Rohit Raja and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-26 with Computers categories.


DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.



Nature Inspired Computation In Data Mining And Machine Learning


Nature Inspired Computation In Data Mining And Machine Learning
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Author : Xin-She Yang
language : en
Publisher: Springer Nature
Release Date : 2019-09-03

Nature Inspired Computation In Data Mining And Machine Learning written by Xin-She Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-03 with Technology & Engineering categories.


This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.



Communication Networks And Service Management In The Era Of Artificial Intelligence And Machine Learning


Communication Networks And Service Management In The Era Of Artificial Intelligence And Machine Learning
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Author : Nur Zincir-Heywood
language : en
Publisher: John Wiley & Sons
Release Date : 2021-10-12

Communication Networks And Service Management In The Era Of Artificial Intelligence And Machine Learning written by Nur Zincir-Heywood and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Technology & Engineering categories.


COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.



Artificial Intelligence And Data Mining Approaches In Security Frameworks


Artificial Intelligence And Data Mining Approaches In Security Frameworks
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Author : Neeraj Bhargava
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-11

Artificial Intelligence And Data Mining Approaches In Security Frameworks written by Neeraj Bhargava and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-11 with Technology & Engineering categories.


ARTIFICIAL INTELLIGENCE AND DATA MINING IN SECURITY FRAMEWORKS Written and edited by a team of experts in the field, this outstanding new volume offers solutions to the problems of security, outlining the concepts behind allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to artificial intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalized security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and data mining and several other computing technologies to deploy such a system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library. This groundbreaking new volume: Clarifies the understanding of certain key mechanisms of technology helpful in the use of artificial intelligence and data mining in security frameworks Covers practical approaches to the problems engineers face in working in this field, focusing on the applications used every day Contains numerous examples, offering critical solutions to engineers and scientists Presents these new applications of AI and data mining that are of prime importance to human civilization as a whole