• Fri frakt över 249 kr
  • •
  • Snabba leveranser
  • •
  • Billiga böcker
Kundservice

Du är på sajten för privatpersoner.

Företag, bibliotek eller offentlig verksamhet?

Du handlar på classic.bokus.com, där alla dina funktioner finns intakta.
Till classic.bokus.com
Bokus logotyp. Gå till startsidan.
  • Erbjudanden
  • Student
  • Topplistor
  • Barn & ungdom
  • Bokus Play
  • E-böcker
  • Ljudböcker
  • Pocketböcker
  • Spel och pussel

Pocketfynda! Hundratals böcker för 49 kr/st →

Sidfot

Mina sidor

    Hjälp

    • Kundservice
    • Vanliga frågor och svar
    • Frakt och leverans
    • Retur vid ångerrätt
    • Reklamera vara
    • Betalning
    • Köpvillkor
    • Allmänna villkor
    • Information om webbplatsens tillgänglighet

    Om Bokus

    • Om oss
    • Pressrum
    • För studenter
    • För företag
    • För bibliotek och offentlig verksamhet
    • För leverantörer
    • Hållbarhet

    Populärt

    • Aktuella erbjudanden
    • Presentkort
    • Studentlitteratur
    • Nya böcker
    • Topplistor
    • Signerade böcker
    • Engelska böcker

    Inspiration

    • Boktips
    • BookTok
    • Barnbokskaraktärer
    • Populära författare
    Logotyp för Bokus
    Följ oss på Facebook (extern länk)Följ oss på Instagram (extern länk)Följ oss på YouTube (extern länk)Följ oss på TikTok (extern länk)
    bokus @ CookiesAnpassa cookiesIntegritetspolicyKöpvillkor
    Till Citymail hemsida (extern länk)Till Budbee hemsida (extern länk)Till Postnord hemsida (extern länk)Till Schenker hemsida (extern länk)Till Early Bird hemsida (extern länk)Till Walleys hemsida (extern länk)
    1. Data och IT
    2. Databaser

    Decision-Making Models

    A Perspective of Fuzzy Logic and Machine Learning

    AvAllahviranloo,Tofig,Tofigh Allahviranloo

    Häftad, Engelska, 2024

    Del i serien Uncertainty, Computational Techniques, and Decision Intelligence

    1 440 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems.

    Other areas of note include optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision-making mechanisms realized under uncertainty.

    • Introduces mathematics of intelligent systems which provides the usage of mathematical rigor such as precise definitions, theorems, results, and proofs
    • Provides extended and new comprehensive methods which can be used efficiently in a fuzzy environment as well as optimization problems and related fields
    • Covers applications and elaborates on the usage of the developed methodology in various fields of industry such as software technologies, biomedicine, image processing, and communications

    Produktinformation

    • Utgivningsdatum:2024-07-25
    • Mått:191 x 235 x 35 mm
    • Vikt:1 420 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Uncertainty, Computational Techniques, and Decision Intelligence
    • Antal sidor:678
    • Förlag:Elsevier Science
    • ISBN:9780443161476

    Utforska kategorier

    • Databaser inom Data och IT
    • Artificiell intelligens inom Data och IT
    • Programmeringsböcker inom Data och IT

    Mer om författaren

    Tofigh Allahviranloo is a full professor of applied mathematics at Istinye University, Turkey. As a trained mathematician and computer scientist, Prof. Allahviranloo has developed a passion for multi- and interdisciplinary research. He is not only deeply involved in fundamental research in fuzzy applied mathematics, especially fuzzy differential equations, but he also aims at innovative applications in the applied biological sciences. He is the author of several books and many papers published by Elsevier and Springer. He actively serves the research community, as Editor-in-Chief of the International J. of Industrial Mathematics, and Associate Editor or editorial board member of several other journals, including Information Sciences, Fuzzy Sets and Systems, Journal of Intelligent and Fuzzy Systems, Iranian J. of Fuzzy Systems and Mathematical Sciences. Dr. Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in computational intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. In 2012 he was elected a fellow of the Royal Society of Canada. His main research directions involve computational intelligence, fuzzy modeling and granular computing, knowledge discovery and data science, pattern recognition, data science, knowledge-based neural networks, and control engineering. He is also an author of 18 research monographs and edited volumes covering various aspects of computational intelligence, data mining, and software engineering. Dr. Pedrycz is vigorously involved in editorial activities. He is the editor-in-chief of Information Sciences, editor-in-chief of WIREs Data Mining and Knowledge Discovery, and co-editor-in-chief of International Journal of Granular Computing, and Journal of Data Information and Management. He serves on the advisory board of IEEE Transactions on Fuzzy Systems.Amir Seyyedabbasi is an assistant professor of software engineering at İstinye University, Turkey. He received his B.Sc., M.Sc., and Ph.D. degrees in computer engineering. His research interests include optimization algorithms, routing protocol design in wireless sensor networks, and IoT. Dr. Seyyedabbasi has several articles in Springer and Elsevier. He serves as a reviewer in some respected journals. He aims to develop and propose new and the hybrid optimization algorithm in engineering.

    Innehållsförteckning

    • Section 1: Decision Making: New Developments1. Neural networks2. Artificial intelligent algorithms, motivation and terminology3. Decision processes4. Learning theorySection 2: Metaheuristic Algorithms5. Nature-inspired algorithms6. Physic-based algorithms7. evolution-based algorithms8. swarm-based algorithms9. Multi-objective algorithms10. Unconstrained / constrained nonlinear optimization11. Evolutionary ComputingSection 3: Optimization Problems12. Mathematical Programming13. Discrete and Combinatorial Optimization14. Optimization and Data Analysis15. Applied optimization problems16. Engineering problemsSection 4: Machine Learning17. Deep Learning18. (Artificial) Neural Networks19. Reinforcement Learning Algorithms20. Classification and clusteringSection 5: Soft Computation21. Uncertainty theory22. Fuzzy sets23. Computation with words24. Soft modelling25. Uncertain optimization models26. Chaos theory and chaotic systemsSection 6: Data Analysis27. Data mining and knowledge discovery28. Categories of techniques of data analysis29. Numerical analysis30. Risk analysisSection 7: Fuzzy Decision System31. Fuzzy Control32. Approximate Reasoning33. Effectiveness in Fuzzy Logics34. Neuro-fuzzy Systems35. Fuzzy rule-based systems