About this ebook
This book explores the cutting-edge integration of AI and neutrosophic statistics, providing powerful tools for analyzing complex data across environmental and material sciences. This book introduces neutrosophic logic, which extends classical logic by incorporating indeterminacy and inconsistency, to enhance AI models. It offers robust methods for decision-making and prediction, addressing uncertainties in data. Designed for researchers, practitioners, and students, this book bridges the gap between theory and practice, offering practical insights for intelligent analysis. By integrating neutrosophic logic with AI, it opens new avenues for handling incomplete and ambiguous data, making it an essential resource for those working with complex datasets. This book is a valuable addition to the literature on AI and statistics, providing readers with the tools and knowledge needed to navigate the complexities of data-driven research and development.
This book explores the cutting-edge integration of AI and neutrosophic statistics, providing powerful tools for analyzing complex data across environmental and material sciences. This book introduces neutrosophic logic, which extends classical logic by incorporating indeterminacy and inconsistenc...
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About the author
Mr Usama Afzal, a PhD researcher at Tianjin University's School of Microelectronics, China, excels in microelectronics, environmental science, material statistics, and physics. His research, centered on material science, nanotechnology, and statistical system analysis, particularly focuses on developing advanced sensors for heavy metal detection. His innovative contributions have been published in prestigious journals and recognized through books and book chapters. As a respected leader in his field, Afzal inspires future researchers with his dedication to advancing sensor technology. He also serves as a book editor for numerous publishing houses, including Cambridge Scholars Publishing, significantly contributing to the scientific community.
Prof Muhammad Aslam pioneered the field of neutrosophic statistical quality control. He is the founder of several key areas in neutrosophic statistics, including neutrosophic inferential statistics, advanced neutrosophic distribution theory, neutrosophic survey sampling, neutrosophic design of experiments, neutrosophic reliability analysis, and neutrosophic index numbers. His contributions have been instrumental in developing the theoretical framework of neutrosophic statistics for inspection, inference, and process control. He originally formulated these concepts and expanded the theory across multiple domains within neutrosophic statistics.
Mr Usama Afzal, a PhD researcher at Tianjin University's School of Microelectronics, China, excels in microelectronics, environmental science, material statistics, and physics. His research, centered on material science, nanotechnology, and statistical system analysis, particularly focuses on dev...
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