Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing

Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing PDF Author: Sujata Dash
Publisher: Springer Nature
ISBN: 3030756572
Category : Technology & Engineering
Languages : en
Pages : 443

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Book Description
This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and its application areas. These computing methods also play a significant role in the design and optimization in diverse engineering disciplines. With the influence and the development of the Internet of things (IoT) concept, the need for using soft computing techniques has become more significant than ever. In general, soft computing methods are closely similar to biological processes than traditional techniques, which are mostly based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis. Soft computing techniques are anticipated to complement each other. The aim of these techniques is to accept imprecision, uncertainties, and approximations to get a rapid solution. However, recent advancements in representation soft computing algorithms (fuzzy logic,evolutionary computation, machine learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machine–firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine–wavelet (SVM–Wavelet) have emerged as powerful computational models. These have also shown significant success in dealing with massive data analysis for large number of applications. All the researchers and practitioners will be highly benefited those who are working in field of computer engineering, medicine, biology application, signal processing, and mechanical engineering. This book is a good collection of state-of-the-art approaches for soft computing-based applications to various engineering fields. It is very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health. This book is very useful because there is no book in the market which provides a good collection of state-of-the-art methods of soft computing-based models for multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, and biomedical and health informatics.

Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing

Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing PDF Author: Sujata Dash
Publisher: Springer Nature
ISBN: 3030756572
Category : Technology & Engineering
Languages : en
Pages : 443

Get Book Here

Book Description
This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and its application areas. These computing methods also play a significant role in the design and optimization in diverse engineering disciplines. With the influence and the development of the Internet of things (IoT) concept, the need for using soft computing techniques has become more significant than ever. In general, soft computing methods are closely similar to biological processes than traditional techniques, which are mostly based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis. Soft computing techniques are anticipated to complement each other. The aim of these techniques is to accept imprecision, uncertainties, and approximations to get a rapid solution. However, recent advancements in representation soft computing algorithms (fuzzy logic,evolutionary computation, machine learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machine–firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine–wavelet (SVM–Wavelet) have emerged as powerful computational models. These have also shown significant success in dealing with massive data analysis for large number of applications. All the researchers and practitioners will be highly benefited those who are working in field of computer engineering, medicine, biology application, signal processing, and mechanical engineering. This book is a good collection of state-of-the-art approaches for soft computing-based applications to various engineering fields. It is very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health. This book is very useful because there is no book in the market which provides a good collection of state-of-the-art methods of soft computing-based models for multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, and biomedical and health informatics.

Advances on Smart and Soft Computing

Advances on Smart and Soft Computing PDF Author: Faisal Saeed
Publisher: Springer Nature
ISBN: 9811655596
Category : Technology & Engineering
Languages : en
Pages : 526

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Book Description
This book presents the papers included in the proceedings of the 2nd International Conference of Advanced Computing and Informatics (ICACIn’21) that was held in Casablanca, Morocco, on May 24–25, 2021. The main theme of the book is “Advances on Smart and Soft Computing.” A total of 71 papers were submitted to the conference, but only 44 papers were accepted and published in this book. The book presents several hot research topics which include artificial intelligence and data science, big data analytics, Internet of Things (IoT), information security, cloud computing, networking and computational informatics.

Computational Intelligence for Medical Internet of Things (MIoT) Applications

Computational Intelligence for Medical Internet of Things (MIoT) Applications PDF Author: Yassine Maleh
Publisher: Elsevier
ISBN: 0323950973
Category : Technology & Engineering
Languages : en
Pages : 374

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Book Description
Computational Intelligence for Medical Internet of Things (MIoT) Applications: Machine Intelligence Applications for IoT in Healthcare explores machine intelligence techniques necessary for effective MIoT research and practice, taking a practical approach for practitioners and students entering the field. This book investigates advanced concepts and applications in the MIoT field, guiding readers through emerging developments and future trends. A wide range of international authors guide readers through advanced concepts, including deep learning, neural network, and big data analytic approaches for the classification, indexing, retrieval, analysis, and inferencing of healthcare data. - Presents the state-of-the-art in machine intelligence and related technologies and methodologies for IoT in healthcare - Discusses emerging developments and trends in machine intelligence for business and decision-making strategy in healthcare - Features new models, practical solutions, prototypes, frameworks and technological advances related to machine intelligence for MIoT applications

Artificial Intelligence for Neurological Disorders

Artificial Intelligence for Neurological Disorders PDF Author: Ajith Abraham
Publisher: Academic Press
ISBN: 0323902782
Category : Medical
Languages : en
Pages : 434

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Book Description
Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances. - Discusses various AI and ML methods to apply for neurological research - Explores Deep Learning techniques for brain MRI images - Covers AI techniques for the early detection of neurological diseases and seizure prediction - Examines cognitive therapies using AI and Deep Learning methods

Advanced Computing Techniques for Optimization in Cloud

Advanced Computing Techniques for Optimization in Cloud PDF Author: H S Madhusudhan
Publisher: CRC Press
ISBN: 1040112641
Category : Computers
Languages : en
Pages : 263

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Book Description
This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques. Focuses on virtual machine placement and migration techniques for cloud data centers Presents the role of machine learning and metaheuristic approaches for optimisation in cloud computing services Includes application of placement techniques for quality of service, performance, and reliability improvement Explores data center resource management, load balancing and orchestration using machine learning techniques Analyses dynamic and scalable resource scheduling with a focus on resource management The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.

Cloud and Edge Networking

Cloud and Edge Networking PDF Author: Kamel Haddadou
Publisher: John Wiley & Sons
ISBN: 1789451280
Category : Computers
Languages : en
Pages : 308

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Book Description
A major transformation in the world of networks is underway, as the focus shifts from physical technology to software-based solutions. In this book, the authors present this new generation of networks that are based in the Cloud by detailing the transition from a complex environment to a simple digital infrastructure. This infrastructure brings together connected devices, the antennas that collect radio waves, the optical fibers that carry signals and the data center that handles all of the different processes. From this perspective, the data center becomes the brain, managing network services, controls, automation, intelligence, security and other applications. This architecture is relevant to carrier networks, the Internet of Things, enterprise networks and the global networks of the major Internet companies. Cloud and Edge Networking further discusses developments at the border of networks, the Edge, where data is processed as near as possible to the source. Over the next ten years, the Edge will become a major strategic factor.

Bio-Inspired Intelligence for Smart Decision-Making

Bio-Inspired Intelligence for Smart Decision-Making PDF Author: Jaganathan, Ramkumar
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 355

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Book Description
In today's complex and fast-paced world, decision-making is critical to problem-solving across industries and academia. However, traditional optimization techniques often need help to cope with the challenges posed by dynamic and intricate environments. This limitation hampers decision-makers' ability to tackle complex problems and seize opportunities effectively. As such, there is a pressing need for innovative approaches that can enhance decision-making processes, enabling individuals and organizations to navigate uncertainty and achieve optimal outcomes. Bio-Inspired Intelligence for Smart Decision-Making offers a compelling solution to this challenge. By exploring the intersection of bio-inspired optimization techniques and decision-making, this book presents a fresh perspective that can revolutionize decisions. The book introduces readers to powerful bio-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies through a multidisciplinary lens that encompasses computer science, artificial intelligence, optimization, and decision science. These algorithms mimic natural systems' efficiency and adaptability, offering a robust framework for researchers, graduate students, and professionals who are addressing complex decision-making problems in diverse fields.

Engineering Applications of Modern Metaheuristics

Engineering Applications of Modern Metaheuristics PDF Author: Taymaz Akan
Publisher: Springer Nature
ISBN: 3031168321
Category : Technology & Engineering
Languages : en
Pages : 209

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Book Description
This book is a collection of various methodologies that make it possible for metaheuristics and hyper-heuristics to solve problems that occur in the real world. This book contains chapters that make use of metaheuristics techniques. The application fields range from image processing to transmission power control, and case studies and literature reviews are included to assist the reader. Furthermore, some chapters present cutting-edge methods for load frequency control and IoT implementations. In this sense, the book offers both theoretical and practical contents in the form of metaheuristic algorithms. The researchers used several stochastic optimization methods in this book, including evolutionary algorithms and Swarm-based algorithms. The chapters were written from a scientific standpoint. As a result, the book is primarily aimed at undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, but it can also be used in courses on Artificial Intelligence, among other things. Similarly, the material may be beneficial to research in evolutionary computation and artificial intelligence communities.

Towards a Wireless Connected World: Achievements and New Technologies

Towards a Wireless Connected World: Achievements and New Technologies PDF Author: Al-Sakib Khan Pathan
Publisher: Springer Nature
ISBN: 3031043219
Category : Technology & Engineering
Languages : en
Pages : 340

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Book Description
This book gathers key advances in various areas related to using wireless Internet and wireless connectivity to achieve a more connected world. The world is now highly dependent on Internet connectivity. Even though some parts of the globe remain isolated, the smoothly running world all around us relies on Internet services for countless businesses and activities. During the COVID-19 pandemic, we have seen that exclusively relying on wired Internet would leave out a large part of our tech-savvy world. Hence, wireless connectivity is essential to anywhere, anytime connectivity. Further, in the event of a new pandemic or other disaster of global scale, wireless Internet offers a reliable way to keep us all connected. The contributors to this book, hailing from academia, industrial and research laboratories, report on the latest solutions, trends and technologies with the potential to make wireless Internet more reliable and secure for the years to come.

Enabling Technologies for Effective Planning and Management in Sustainable Smart Cities

Enabling Technologies for Effective Planning and Management in Sustainable Smart Cities PDF Author: Mohd Abdul Ahad
Publisher: Springer Nature
ISBN: 3031229223
Category : Computers
Languages : en
Pages : 409

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Book Description
With the rapid penetration of technology in varied application domains, the existing cities are getting connected more seamlessly. Cities becomes smart by inducing ICT in the classical city infrastructure for its management. According to McKenzie Report, about 68% of the world population will migrate towards urban settlements in near future. This migration is largely because of the improved Quality of Life (QoL) and livelihood in urban settlements. In the light of urbanization, climate change, democratic flaws, and rising urban welfare expenditures, smart cities have emerged as an important approach for society’s future development. Smart cities have achieved enhanced QoL by giving smart information to people regarding healthcare, transportation, smart parking, smart traffic structure, smart home, smart agronomy, community security etc. Typically, in smart cities data is sensed by the sensor devices and provided to end users for further use. The sensitive data is transferred with the help of internet creating higher chances for the adversaries to breach the data. Considering the privacy and security as the area of prime focus, this book covers the most prominent security vulnerabilities associated with varied application areas like healthcare, manufacturing, transportation, education and agriculture etc. Furthermore, the massive amount of data being generated through ubiquitous sensors placed across the smart cities needs to be handled in an effective, efficient, secured and privacy preserved manner. Since a typical smart city ecosystem is data driven, it is imperative to manage this data in an optimal manner. Enabling technologies like Internet of Things (IoT), Natural Language Processing (NLP), Blockchain Technology, Deep Learning, Machine Learning, Computer vision, Big Data Analytics, Next Generation Networks and Software Defined Networks (SDN) provide exemplary benefits if they are integrated in the classical city ecosystem in an effective manner. The application of Artificial Intelligence (AI) is expanding across many domains in the smart city, such as infrastructure, transportation, environmental protection, power and energy, privacy and security, governance, data management, healthcare, and more. AI has the potential to improve human health, prosperity, and happiness by reducing our reliance on manual labor and accelerating our progress in the sciences and technologies. NLP is an extensive domain of AI and is used in collaboration with machine learning and deep learning algorithms for clinical informatics and data processing. In modern smart cities, blockchain provides a complete framework that controls the city operations and ensures that they are managed as effectively as possible. Besides having an impact on our daily lives, it also facilitates many areas of city management.