Bio Inspired Computing Models And Algorithms
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Bio Inspired Computing Models And Algorithms
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Author : Tao Song
language : en
Publisher: World Scientific
Release Date : 2019-04-05
Bio Inspired Computing Models And Algorithms written by Tao Song and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-05 with Computers categories.
Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics.The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems.Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well.
Bio Inspired Computing Models And Algorithms
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Author : Tao Song
language : en
Publisher:
Release Date : 2018
Bio Inspired Computing Models And Algorithms written by Tao Song and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Natural computation categories.
Bio Inspired Neurocomputing
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Author : Akash Kumar Bhoi
language : en
Publisher: Springer Nature
Release Date : 2020-07-21
Bio Inspired Neurocomputing written by Akash Kumar Bhoi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-21 with Technology & Engineering categories.
This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.
Bio Inspired Algorithms In Machine Learning And Deep Learning For Disease Detection
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Author : Balasubramaniam S
language : en
Publisher: CRC Press
Release Date : 2025-03-13
Bio Inspired Algorithms In Machine Learning And Deep Learning For Disease Detection written by Balasubramaniam S and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Technology & Engineering categories.
Currently, computational intelligence approaches are utilised in various science and engineering applications to analyse information, make decisions, and achieve optimisation goals. Over the past few decades, various techniques and algorithms have been created in disciplines such as genetic algorithms, artificial neural networks, evolutionary algorithms, and fuzzy algorithms. In the coming years, intelligent optimisation algorithms are anticipated to become more efficient in addressing various issues in engineering, scientific, medical, space, and artificial satellite fields, particularly in early disease diagnosis. A metaheuristic in computer science is designed to discover optimisation algorithms capable of solving intricate issues. Metaheuristics are optimisation algorithms that mimic biological behaviours of animals or birds and are utilised to discover the best solution for a certain problem. A meta-heuristic is an advanced approach used by heuristics to tackle intricate optimisation problems. A metaheuristic in mathematical programming is a method that seeks a solution to an optimisation problem. Metaheuristics utilise a heuristic function to assist in the search process. Heuristic search can be categorised as blind search or informed search. Meta-heuristic optimisation algorithms are gaining popularity in various applications due to their simplicity, independence from data trends, ability to find optimal solutions, and versatility across different fields. Recently, many nature-inspired computation algorithms have been utilised to diagnose people with different diseases. Nature-inspired methodologies are now widely utilised across several fields for tasks such as data analysis, decision-making, and optimisation. Techniques inspired by nature are categorised as either biology-based or natural phenomena-based. Bioinspired computing encompasses various topics in computer science, mathematics, and biology in recent years. Bio-inspired computer optimisation algorithms are a developing method that utilises concepts and inspiration from biological development to create new and resilient competitive strategies. Bio-inspired optimisation algorithms have gained recognition in machine learning and deep learning for solving complicated issues in science and engineering. Utilising BIAs learning methods with machine learning and deep learning shows great promise for accurately classifying medical conditions. This book explores the historical development of bio-inspired algorithms and their application in machine learning and deep learning models for disease diagnosis, including COVID-19, heart diseases, cancer, diabetes and some other diseases. It discusses the advantages of using bio-inspired algorithms in disease diagnosis and concludes with research directions and future prospects in this field.
High Performance Computing In Biomimetics
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Author : Kamarul Arifin Ahmad
language : en
Publisher: Springer Nature
Release Date : 2024-03-20
High Performance Computing In Biomimetics written by Kamarul Arifin Ahmad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-20 with Technology & Engineering categories.
This book gives a complete overview of current developments in the implementation of high performance computing (HPC) in various biomimetic technologies. The book presents various topics that are subdivided into the following parts: A) biomimetic models and mechanics; B) locomotion and computational methods; C) distributed computing and its evolution; D) distributed and parallel computing architecture; E) high performance computing and biomimetics; F) big data, management, and visualization; and G) future of high performance computing in biomimetics. This book presents diverse computational technologies to model and replicate biologically inspired design for the purpose of solving complex human problems. The content of this book is presented in a simple and lucid style which can also be used by professionals, non-professionals, scientists, and students who are interested in the research area of high performance computing applications in the development of biomimetics technologies.
Contemporary Computing
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Author : Srinivas Aluru
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-07-06
Contemporary Computing written by Srinivas Aluru 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 2011-07-06 with Computers categories.
This volume constitutes the refereed proceedings of the Fourth International Conference on Contemporary Computing, IC3 2010, held in Noida, India, in August 2011. The 58 revised full papers presented were carefully reviewed and selected from 175 submissions.
Membrane Computing Models Implementations
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Author : Gexiang Zhang
language : en
Publisher: Springer Nature
Release Date : 2021-07-01
Membrane Computing Models Implementations written by Gexiang Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-01 with Computers categories.
The theoretical basis of membrane computing was established in the early 2000s with fundamental research into the computational power, complexity aspects and relationships with other (un)conventional computing paradigms. Although this core theoretical research has continued to grow rapidly and vigorously, another area of investigation has since been added, focusing on the applications of this model in many areas, most prominently in systems and synthetic biology, engineering optimization, power system fault diagnosis and mobile robot controller design. The further development of these applications and their broad adoption by other researchers, as well as the expansion of the membrane computing modelling paradigm to other applications, call for a set of robust, efficient, reliable and easy-to-use tools supporting the most significant membrane computing models. This work provides comprehensive descriptions of such tools, making it a valuable resource for anyone interested in membrane computing models.
Bio Inspired Computing Theories And Applications
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Author : Cheng He
language : en
Publisher: Springer
Release Date : 2017-11-10
Bio Inspired Computing Theories And Applications written by Cheng He and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-10 with Computers categories.
This book constitutes the proceedings of the 12th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2017, held in Harbin, China, December 2017. The 50 full papers presented were selected from 143 submissions. The papers deal with studies abstracting computing ideas such as data structures, operations with data, ways to control operations, computing models from living phenomena or biological systems such as evolution, cells, tissues, neural networks, immune systems, and ant colonies.
Bio Inspired Computing Theories And Applications
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Author : Jianyong Qiao
language : en
Publisher: Springer
Release Date : 2018-10-17
Bio Inspired Computing Theories And Applications written by Jianyong Qiao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-17 with Computers categories.
This two-volume set (CCIS 951 and CCIS 952) constitutes the proceedings of the 13th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2018, held in Beijing, China, in November 2018. The 88 full papers presented in both volumes were selected from 206 submissions. The papers deal with studies abstracting computing ideas such as data structures, operations with data, ways to control operations, computing models from living phenomena or biological systems such as evolution, cells, neural networks, immune systems, swarm intelligence.
The Future Of Artificial Intelligence Computational Intelligence Ethical Frameworks And Societal Impact
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Author : Dr. Ankush Tulshiram Aundhakar
language : en
Publisher: Libros Publication
Release Date : 2026-01-21
The Future Of Artificial Intelligence Computational Intelligence Ethical Frameworks And Societal Impact written by Dr. Ankush Tulshiram Aundhakar and has been published by Libros Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-21 with Computers categories.
The Future of Artificial Intelligence: Computational Intelligence, Ethical Frameworks, and Societal Impact presents a comprehensive and interdisciplinary examination of artificial intelligence as both a technological advancement and a transformative force shaping contemporary society. As AI systems increasingly influence decision-making, governance, economic structures, and human interaction, the need for a balanced understanding that integrates technical foundations with ethical and social considerations has become essential. This book addresses that need by offering a holistic perspective on how artificial intelligence is developed, applied, and governed in real-world contexts. The book explores artificial intelligence from its conceptual roots to its modern implementations, emphasizing how intelligent behavior emerges from computational intelligence, adaptive learning, and data-driven systems. It examines the mechanisms through which machines learn, reason under uncertainty, and support complex decision-making processes. By focusing on machine learning, deep learning, and bio inspired computational models, the book explains how AI systems achieve performance, adaptability, and scalability across diverse domains. Beyond technical foundations, the book critically engages with the ethical dimensions of artificial intelligence. It highlights key concerns related to transparency, explainability, accountability, fairness, and human autonomy. Rather than treating ethics as an external constraint, the book integrates ethical reasoning into the discussion of AI design and deployment, emphasizing that responsible innovation is central to sustainable technological progress. Ethical frameworks are presented as practical tools for guiding decisions in environments where AI systems have significant social impact. A central theme of the book is the relationship between artificial intelligence and society. It examines how AI reshapes work, education, healthcare, public services, and cultural practices, while also addressing challenges such as inequality, digital divides, and access to technology. The book emphasizes that AI is not a neutral force but a socio-technical system shaped by human choices, institutional structures, and cultural values. Understanding this relationship is essential for ensuring that AI contributes to inclusive and equitable social development. The book also addresses the policy and governance challenges associated with the global expansion of artificial intelligence. It considers the need for legal accountability, regulatory balance, and international cooperation in managing AI technologies that operate across borders. By examining governance from both national and global perspectives, the book highlights the importance of aligning innovation with public trust and societal responsibility. Looking toward the future, the book explores emerging trends in artificial intelligence, including increasing autonomy, human-centered and collaborative systems, and the convergence of AI with other advanced technologies. It emphasizes ethical foresight and longterm thinking as essential components of guiding AI development in ways that support human dignity, environmental sustainability, and social resilience. Written in a clear and scholarly style, this book is intended for researchers, students, educators, policymakers, and practitioners seeking a deep and reflective understanding of artificial intelligence. The Future of Artificial Intelligence offers not only technical insight but also ethical and societal guidance, positioning AI as a tool that must be shaped deliberately and responsibly to serve human and collective well-being in an increasingly automated world.