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_aLecture Notes in Data Engineering, Computational Intelligence, and Decision-Making, Volume 1 _h[electronic resource] : _b2024 International Scientific Conference "Intelligent Systems of Decision-Making and Problems of Computational Intelligence", Proceedings / _cedited by Sergii Babichev, Volodymyr Lytvynenko. |
250 | _a1st ed. 2024. | ||
264 | 1 |
_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2024. |
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300 |
_aXV, 432 p. 280 illus., 221 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes on Data Engineering and Communications Technologies, _x2367-4520 ; _v219 |
|
505 | 0 | _aBasic Concept of Magnetic Materials and Summary of all the Chapters -- Magnetic Materials: Fundamentals and Applications -- Units, Dimensions and Conversion Factors in Magnetism: Basic Understanding -- Classification of Ferrites, Synthesis and Properties of Spinel Ferrite Nanoparticles and Their Applications -- Applications of Magnetic Materials -- Defects-Induced Multifunctional Properties in BiFeO3 -- Basic Concepts of Nitride Magnetic Materials and their Applications -- Fundamental Aspects of Nanomagnetism and its Versatile Applications -- Ferromagnetic Functional Materials -- Origin of Magnetism, Synthesis, Characterization and Perspective Application of Magnetic Graphene -- Externally Driven Interface in Three Dimensional Ising Model: A Monte Carlo study -- Selected Examples of Iron and Cobalt Complexes Exhibiting Spin-Crossover Behavior -- Magnetism in Bulk and Thin Film Metallic Glass Systems -- Recent Developments in Magnetic Nanocrystalline Metal Oxides and their Biomedical Applications -- Ferromagnetism in Two-Dimensional TMD Materials via Doping, Phase Transition and Defect Engineering. | |
520 | _aThis book addresses contemporary challenges in artificial and computational intelligence, particularly focusing on decision-making systems. It explores current trends in computer science, including the collection, analysis, and processing of information. The advancement of modern information and computer technologies for data analysis and processing in data mining and machine learning is highlighted, showcasing their role in enhancing the efficiency of information processing by reducing time and increasing accuracy. The book comprises 37 scientific papers presenting cutting-edge research in data mining, machine learning, and decision-making. It is categorized into three sections: 1. Analysis and modeling of hybrid systems and processes-14 papers. 2. Theoretical and applied aspects of decision-making systems-7 papers. 3. Data engineering, computational intelligence, and inductive modeling-16 papers. This book is designed for scientists and developers specializing in data mining, machine learning, and decision-making systems. | ||
541 |
_fUABC ; _cPerpetuidad |
||
650 | 0 | _aComputational intelligence. | |
650 | 0 | _aArtificial intelligence. | |
650 | 1 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aArtificial Intelligence. |
700 | 1 |
_aBabichev, Sergii. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aLytvynenko, Volodymyr. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
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773 | 0 | _tSpringer Nature eBook | |
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_iPrinted edition: _z9783031709586 |
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_iPrinted edition: _z9783031709609 |
830 | 0 |
_aLecture Notes on Data Engineering and Communications Technologies, _x2367-4520 ; _v219 |
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_zLibro electrónico _uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-70959-3 |
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