Modern Superhypersoft Computing Trends In Science And Technology
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Modern Superhypersoft Computing Trends In Science And Technology
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Author : Smarandache, Florentin
language : en
Publisher: IGI Global
Release Date : 2024-12-13
Modern Superhypersoft Computing Trends In Science And Technology written by Smarandache, Florentin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-13 with Computers categories.
In today's data-rich environment, traditional decision-making methods often fail to address the complexities of real-world challenges, especially under conditions of uncertainty and ambiguity. Advanced computational frameworks like neutrosophic and plithogenic theories provide innovative solutions for more nuanced analysis and effective decision-making. These methodologies support better outcomes in areas like knowledge management, economics, and strategic planning by accommodating multiple criteria and incomplete information. By leveraging these sophisticated tools, decision-makers can enhance their ability to adapt to complex scenarios. This shift is crucial for advancing research and technology in a rapidly evolving landscape. Modern SuperHyperSoft Computing Trends in Science and Technology explores the use of advanced computational theories, such as neutrosophic, plithogenic, and SuperHyperSoft set theories, to enhance decision-making processes across various scientific and technological fields. It features contributions that apply these frameworks to complex problems. Covering topics such as artificial intelligence (AI), quality assessment, and wastewater treatment, this book is an excellent resource for students, faculty, researchers, engineers, decision-makers, and more.
Exploring The Fusion Of Quantum Computing And Machine Learning
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Author : R.I., Minu
language : en
Publisher: IGI Global
Release Date : 2025-04-17
Exploring The Fusion Of Quantum Computing And Machine Learning written by R.I., Minu and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-17 with Computers categories.
The fusion of quantum computing and machine learning holds the potential to revolutionize how we solve complex problems. Quantum computing, with its ability to process vast amounts of data through the principles of quantum mechanics, could accelerate machine learning algorithms, enabling faster and more efficient pattern recognition, optimization, and decision-making. This convergence helps overcome limitations faced by classical computing in fields like artificial intelligence, drug discovery, cryptography, and more. As researchers continue to explore this fusion, the potential applications of quantum-enhanced machine learning increase, opening new possibilities for innovation and problem-solving across industries. Exploring the Fusion of Quantum Computing and Machine Learning explores the revolutionary fusion of quantum computing and machine learning. It examines practical applications, demonstrating how the integration of quantum computing and machine learning algorithms can reveal new solutions for complex problems, paving the way for advancements in various fields. This book covers topics such as neural networks, online marketing, and quantum systems, and is a useful resource for computer engineers, energy scientists, marketers, business owners, medical professionals, academicians, and researchers.
Advancing Cyber Threat Detection Through Quantum And Edge Computing
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Author : Joseph, Shenson
language : en
Publisher: IGI Global
Release Date : 2025-08-12
Advancing Cyber Threat Detection Through Quantum And Edge Computing written by Joseph, Shenson and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-12 with Computers categories.
As cyber threats grow in scale, sophistication, and frequency, traditional detection methods struggle to keep pace. To address this landscape, researchers and organizations turn to emerging technologies like quantum computing and edge computing. Quantum computing offers increased processing power, capable of analyzing complex data patterns and encryptions. Meanwhile, edge computing enables real-time threat detection and increases response times. By combining these two technologies, it creates smarter, faster, and more adaptive cybersecurity systems. Further exploration into how the convergence of quantum and edge computing can revolutionize cyber threat detection may pave the way for more resilient defense mechanisms in the digital age. Advancing Cyber Threat Detection Through Quantum and Edge Computing explores how quantum computing and artificial intelligence (AI) reshape the landscape of real-time anomaly detection, predictive analytics, and next-gen cybersecurity. It examines how quantum-enhanced AI models can detect patterns, adapt to emerging threats, and revolutionize security frameworks across industries, from finance and healthcare to national security and cloud infrastructure. This book covers topics such as blockchain, threat intelligence, and neural networks, and is a useful resource for computer engineers, security professionals, academicians, researchers, and data scientists.
Neural Networks And Graph Models For Traffic And Energy Systems
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Author : Bhambri, Pankaj
language : en
Publisher: IGI Global
Release Date : 2025-02-21
Neural Networks And Graph Models For Traffic And Energy Systems written by Bhambri, Pankaj and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-21 with Computers categories.
Neural networks and graph models play a transformative role in optimizing traffic and energy systems, offering advanced solutions for managing complex, interconnected infrastructures. Neural networks can predict traffic patterns, optimize routes, and improve the efficiency of energy distribution networks by learning from real-time data. Graph models help represent and analyze the relationships and flows within transportation and energy systems, enabling more accurate modeling of networks and their interactions. Together, these technologies allow for smarter traffic management, reduced congestion, and enhanced energy grid efficiency. As cities and industries continue to grow, integrating neural networks and graph models into traffic and energy systems is essential in creating sustainable, efficient, and resilient urban environments. Neural Networks and Graph Models for Traffic and Energy Systems explores the sophisticated techniques and practical uses of artificial intelligence in improving and overseeing traffic and energy networks. It examines the connection between neural networks and graph theory, showing how these technologies might transform the effectiveness, sustainability, and robustness of urban infrastructure. This book covers topics such as sustainable development, energy science, traffic systems, and is a useful resource for energy scientists, computer engineers, urban developers, academicians, and researchers.
Ai Driven Solutions For Solar Energy Efficiency Irradiance Modeling And Pv Forecasting
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Author : Alexandria, Auzuir Ripardo de
language : en
Publisher: IGI Global
Release Date : 2025-08-08
Ai Driven Solutions For Solar Energy Efficiency Irradiance Modeling And Pv Forecasting written by Alexandria, Auzuir Ripardo de and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-08 with Technology & Engineering categories.
The issue of intermittency, or variations in solar irradiance caused by weather, time of day, and geographic considerations, confronts the solar energy industry. Because of this unpredictability, precise forecasting and effective management of solar power generation are essential for a steady supply of energy. Simultaneously, artificial intelligence (AI) approaches, in particular machine learning (ML), deep learning (DL), and neural networks, have shown promise in resolving intricate, nonlinear issues across a range of areas. However, the utilization of these technologies for projecting solar irradiance and optimizing energy management is yet to be explored in depth, necessitating specific skills and methods to properly tap into their potential. AI-Driven Solutions for Solar Energy Efficiency, Irradiance Modeling, and PV Forecasting examines the relationship between solar energy and AI, with a particular emphasis on how AI-driven methods can improve solar power systems' performance, efficiency, and forecasting. It illustrates how AI-based optimization algorithms may maximize energy output and reduce losses in photovoltaic (PV) systems and solar power plants. Covering topics such as charge management, microgrids, and smart building designs, this book is an excellent resource for engineers, executives, policymakers, technologists, environmental advocates, business leaders, investors, professionals, researchers, scholars, academicians, and more.
Neutrosophic Sets And Systems Vol 77 2025
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2025-01-31
Neutrosophic Sets And Systems Vol 77 2025 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-31 with Mathematics categories.
“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. This theory considers every notion or idea together with its opposite or negation
Superhypergraph Neural Networks And Plithogenic Graph Neural Networks Theoretical Foundations
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Author : Takaaki Fujita
language : en
Publisher: Infinite Study
Release Date : 2025-01-01
Superhypergraph Neural Networks And Plithogenic Graph Neural Networks Theoretical Foundations written by Takaaki Fujita and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-01 with Mathematics categories.
Hypergraphs extend traditional graphs by allowing edges to connect multiple nodes, while superhypergraphs further generalize this concept to represent even more complex relationships. Neural networks, inspired by biological systems, are widely used for tasks such as pattern recognition, data classification, and prediction. Graph Neural Networks (GNNs), a well-established framework, have recently been extended to Hypergraph Neural Networks (HGNNs), with their properties and applications being actively studied. The Plithogenic Graph framework enhances graph representations by integrating multi-valued attributes, as well as membership and contradiction functions, enabling the detailed modeling of complex relationships. In the context of handling uncertainty, concepts such as Fuzzy Graphs and Neutrosophic Graphs have gained prominence. It is well established that Plithogenic Graphs serve as a generalization of both Fuzzy Graphs and Neutrosophic Graphs. Furthermore, the Fuzzy Graph Neural Network has been proposed and is an active area of research. This paper establishes the theoretical foundation for the development of SuperHyperGraph Neural Networks (SHGNNs) and Plithogenic Graph Neural Networks, expanding the applicability of neural networks to these advanced graph structures. While mathematical generalizations and proofs are presented, future computational experiments are anticipated.
Advancing Uncertain Combinatorics Through Graphization Hyperization And Uncertainization Fuzzy Neutrosophic Soft Rough And Beyond
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Author : Takaaki Fujita
language : en
Publisher: Infinite Study
Release Date : 2025-01-20
Advancing Uncertain Combinatorics Through Graphization Hyperization And Uncertainization Fuzzy Neutrosophic Soft Rough And Beyond written by Takaaki Fujita and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-20 with Mathematics categories.
This book is the fifth volume in the series of Collected Papers on Advancing Uncertain Combinatorics through Graphization, Hyperization, and Uncertainization: Fuzzy, Neutrosophic, Soft, Rough, and Beyond. This volume specifically delves into the concept of Various SuperHyperConcepts, building on the foundational advancements introduced in previous volumes. The series aims to explore the ongoing evolution of uncertain combinatorics through innovative methodologies such as graphization, hyperization, and uncertainization. These approaches integrate and extend core concepts from fuzzy, neutrosophic, soft, and rough set theories, providing robust frameworks to model and analyze the inherent complexity of real-world uncertainties. At the heart of this series lies combinatorics and set theory—cornerstones of mathematics that address the study of counting, arrangements, and the relationships between collections under defined rules. Traditionally, combinatorics has excelled in solving problems involving uncertainty, while advancements in set theory have expanded its scope to include powerful constructs like fuzzy and neutrosophic sets. These advanced sets bring new dimensions to uncertainty modeling by capturing not just binary truth but also indeterminacy and falsity. In this fifth volume, the exploration of Various SuperHyperConcepts provides an innovative lens to address uncertainty, complexity, and hierarchical relationships. It synthesizes key methodologies introduced in earlier volumes, such as hyperization and neutrosophic extensions, while advancing new theories and applications. From pioneering hyperstructures to applications in advanced decision-making, language modeling, and neural networks, this book represents a significant leap forward in uncertain combinatorics and its practical implications across disciplines. The book is structured into 17 chapters, each contributing unique perspectives and advancements in the realm of Various SuperHyperConcepts and their related frameworks: Chapter 1 introduces the concept of Body-Mind-Soul-Spirit Fluidity within psychology and phenomenology, while examining established social science frameworks like PDCA and DMAIC. It extends these frameworks using Neutrosophic Sets, a flexible extension of Fuzzy Sets, to improve their adaptability for mathematical and programming applications. The chapter emphasizes the potential of Neutrosophic theory to address multi-dimensional challenges in social sciences. Chapter 2 delves into the theoretical foundation of Hyperfunctions and their generalizations, such as Hyperrandomness and Hyperdecision-Making. It explores higher-order frameworks like Weak Hyperstructures, Hypergraphs, and Cognitive Hypermaps, aiming to establish their versatility in addressing multi-layered problems and setting a foundation for further studies. Chapter 3 extends traditional decision-making methodologies into HyperDecision-Making and n-SuperHyperDecision-Making. By building on approaches like MCDM and TOPSIS, this chapter develops frameworks capable of addressing complex decision-making scenarios, emphasizing their applicability in dynamic, multi-objective contexts. Chapter 4 explores integrating uncertainty frameworks, including Fuzzy, Neutrosophic, and Plithogenic Sets, into Large Language Models (LLMs). It proposes innovative models like Large Uncertain Language Models and Natural Uncertain Language Processing, integrating hierarchical and generalized structures to advance the handling of uncertainty in linguistic representation and processing. Chapter 5 introduces the Natural n-Superhyper Plithogenic Language by synthesizing natural language, plithogenic frameworks, and superhyperstructures. This innovative construct seeks to address challenges in advanced linguistic and structural modeling, blending attributes of uncertainty, complexity, and hierarchical abstraction. Chapter 6 defines mathematical extensions such as NeutroHyperstructures and AntiHyperstructures using the Neutrosophic Triplet framework. It formalizes structures like neutro-superhyperstructures, advancing classical frameworks into higher-dimensional realms. Chapter 7 explores the extension of Binary Code, Gray Code, and Floorplans through hyperstructures and superhyperstructures. It highlights their iterative and hierarchical applications, demonstrating their adaptability for complex data encoding and geometric arrangement challenges. Chapter 8 investigates the Neutrosophic TwoFold SuperhyperAlgebra, combining classical algebraic operations with neutrosophic components. This chapter expands upon existing algebraic structures like Hyperalgebra and AntiAlgebra, exploring hybrid frameworks for advanced mathematical modeling. Chapter 9 introduces Hyper Z-Numbers and SuperHyper Z-Numbers by extending the traditional Z-Number framework with hyperstructures. These extensions aim to represent uncertain information in more complex and multidimensional contexts. Chapter 10 revisits category theory through the lens of hypercategories and superhypercategories. By incorporating hierarchical and iterative abstractions, this chapter extends the foundational principles of category theory to more complex and layered structures. Chapter 11 formalizes the concept of n-SuperHyperBranch-width and its theoretical properties. By extending hypergraphs into superhypergraphs, the chapter explores recursive structures and their potential for representing intricate hierarchical relationships. Chapter 12 examines superhyperstructures of partitions, integrals, and spaces, proposing a framework for advancing mathematical abstraction. It highlights the potential applications of these generalizations in addressing hierarchical and multi-layered problems. Chapter 13 revisits Rough, HyperRough, and SuperHyperRough Sets, introducing new concepts like Tree-HyperRough Sets. The chapter connects these frameworks to advanced approaches for modeling uncertainty and complex relationships. Chapter 14 explores Plithogenic SuperHyperStructures and their applications in decision-making, control, and neuro systems. By integrating these advanced frameworks, the chapter proposes innovative directions for extending existing systems to handle multi-attribute and contradictory properties. Chapter 15 focuses on superhypergraphs, expanding hypergraph concepts to model complex structural types like arboreal and molecular superhypergraphs. It introduces Generalized n-th Powersets as a unifying framework for broader mathematical applications, while also touching on hyperlanguage processing. Chapter 16 defines NeutroHypergeometry and AntiHypergeometry as extensions of classical geometric structures. Using the Geometric Neutrosophic Triplet, the chapter demonstrates the flexibility of these frameworks in representing multi-dimensional and uncertain relationships. Chapter 17 establishes the theoretical groundwork for SuperHyperGraph Neural Networks and Plithogenic Graph Neural Networks. By integrating advanced graph structures, this chapter opens pathways for applying neural networks to more intricate and uncertain data representations.
Trends And Perspectives In Modern Computational Science
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Author :
language : en
Publisher:
Release Date : 2006
Trends And Perspectives In Modern Computational Science written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computer science categories.
Advances In Core Computer Science Based Technologies
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Author : George A. Tsihrintzis
language : en
Publisher: Springer Nature
Release Date : 2020-06-18
Advances In Core Computer Science Based Technologies written by George A. Tsihrintzis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-18 with Technology & Engineering categories.
This book introduces readers to some of the most significant advances in core computer science-based technologies. At the dawn of the 4th Industrial Revolution, the field of computer science-based technologies is growing continuously and rapidly, and is developing both in itself and in terms of its applications in many other disciplines. Written by leading experts and consisting of 18 chapters, the book is divided into seven parts: (1) Computer Science-based Technologies in Education, (2) Computer Science-based Technologies in Risk Assessment and Readiness, (3) Computer Science-based Technologies in IoT, Blockchains and Electronic Money, (4) Computer Science-based Technologies in Mobile Computing, (5) Computer Science-based Technologies in Scheduling and Transportation, (6) Computer Science-based Technologies in Medicine and Biology, and (7) Theoretical Advances in Computer Science with Significant Potential Applications in Technology. Featuring an extensive list of bibliographic references at the end of each chapter to help readers probe further into the application areas of interest to them, this book is intended for professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also useful for those from other disciplines wanting to become well versed in some of the latest computer science-based technologies.