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This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and edical image processing and analysis. The book is directed to the Ph.D.
This book focuses on the use of The Internet of Things (IoT) and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. IoT and big data emerged from the early 2000s data boom, driven forward by many of the early internet and technology companies. The Internet of Things (IoT) is an interconnection of several devices, networks, technologies, and human resources to achieve a common goal. There are a variety of IoT-based applications being used in different sectors and have succeeded in providing huge benefits to the users. The generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends to adopt the data analytics to strengthen solutions. The success of IoT depends upon the influential association of big data analytics. New technologies like search engines, mobile devices, and industrial machines provided as much data as companies could handle-and the scale continues to grow. In a study conducted by IDC, the market intelligence firm estimated that the global production of data would grow 10x between 2015 and 2020. So, the proposed book covers up all the aspects in the field discuss above.
This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases.
Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains.
This is the first book on experience-based knowledge representation and knowledge management using the unique Decisional DNA (DDNA) technology.
This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others.Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used in different domains. The book offers a valuable resource for PhD students, Master's and undergraduate students of Information Technology (IT)-related degrees such as Computer Science, Information Systems and Electronic Engineering.
This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice.
In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues.
This research-oriented book presents key contributions on architecting the digital transformation. It includes the following main sections covering 20 chapters: · Digital Transformation · Digital Business · Digital Architecture · Decision Support · Digital Applications Focusing on digital architectures for smart digital products and services, it is a valuable resource for researchers, doctoral students, postgraduates, graduates, undergraduates, academics and practitioners interested in digital transformation.
This book bridges the gap between Soft Computing techniques and their applications to complex engineering problems.
This book presents the latest advances in remote-sensing and geographic information systems and applications.
Biometric and Intelligent Decision Making Support
This book presents innovative theories, methodologies, and techniques in risk management and decision making. Covers multi-criteria decision making, healthcare modeling, supply chain optimisation and resource allocation, business and political risk management.
This book is about the formulations, theoretical investigations, and practical applications of new stochastic models for fundamental concepts and operations of the discipline of risk management.
This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. The book is directed to the Ph.D.
Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data.This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process.
This book focuses on various aspects of research on ageing, including in relation to assistive technology; Products, services and environments have been changing in response to the changing population.Presenting international design research to demonstrate the thinking and ideas shaping design, this book is a valuable resource for designers;
This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications.
Experimental data analysis is at the core of scientific inquiry, and computers have taken this function to a new level. This volume is an interactive guide to complex modern analytical processes from non-linear curve fitting to clustering and machine learning.
This book illustrates the rapid pace of development in intelligent assistive technology in recent years, and highlights some salient examples of using modern IT&C technologies to provide devices, systems and application software for persons with certain motor or cognitive disabilities.
This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns.
This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications.
Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented.
This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of the rough set theory, then examines selected relations between rough set theory and non-classical logics including modal logic.
This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world.
Last, Chapter 7 presents simulation methodologies for modeling maritime traffic. The intended readership of the book spans both an academic audience and professionals in the areas of Operational Research, Transportation Science, and Maritime Science interested in applying IT methodologies in their areas of expertise.
This book presents neuromorphic cognitive systems from a learning and memory-centered perspective.
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