9781041060031 - artificial intelligence techniques in mathematical modeling and optimization (intelligent data-driven systems and artificial intelligence) (16 resultados)
Artificial Intelligence Techniques in Mathematical Modeling and Optimization
Awasthi, Mukesh Kumar (EDT); Kumar, Sanoj (EDT); Saini, Deepika (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 184,16
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Artificial Intelligence Techniques in Mathematical Modeling and Optimization
Awasthi, Mukesh Kumar (EDT); Kumar, Sanoj (EDT); Saini, Deepika (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 216,11
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Condición: As New. Unread book in perfect condition.
Artificial Intelligence Techniques in Mathematical Modeling and Optimization
Awasthi, Mukesh Kumar (EDT); Kumar, Sanoj (EDT); Saini, Deepika (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 215,98
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 233,30
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 251,12
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Condición: New.
Artificial Intelligence Techniques in Mathematical Modeling and Optimization
Awasthi, Mukesh Kumar (EDT); Kumar, Sanoj (EDT); Saini, Deepika (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 237,25
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 253,66
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 257,69
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Librería: moluna, Greven, Alemaniamoluna
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EUR 238,00
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Condición: New.
Artificial Intelligence Techniques in Mathematical Modeling and Optimization
Awasthi, Mukesh Kumar (Editor)/ Kumar, Sanoj (Editor)/ Saini, Deepika (Editor)
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 330,97
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Hardcover. Condición: Brand New. 472 pages. 9.18x6.12x9.45 inches. In Stock.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 333,96
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Buch. Condición: Neu. Neuware - Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between artificial intelligence and mathematical modeling. This edited volume brings together innovative research exploring how AI-driven methods revoluti…onize traditional approaches to complex optimization problems, enabling enhanced performance, interpretability, and real-world applicability across diverse domains.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 186,54
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Hardcover. Condición: new. Hardcover. Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between artificial intelligence and mathematical modeling. This edited volume brings together innovative research exploring how AI-driven methods re…volutionize traditional approaches to complex optimization problems, enabling enhanced performance, interpretability, and real-world applicability across diverse domains.Covering foundational and advanced topics, the book introduces readers to machine learning, deep learning, and reinforcement learning as critical tools for modeling high-dimensional, nonlinear, and stochastic systems. Chapters delve into essential aspects like data pre-processing, feature engineering, neural network architectures, swarm intelligence, quantum optimization, and multi-objective decision-making. Emerging techniques such as Fire Hawk Optimization Plus (FHO+), hybrid deep learning-quantum frameworks, and explainable AI (XAI) are discussed in the context of real-world scenarios ranging from energy systems and manufacturing to disaster prediction and healthcare analytics.This volume uniquely bridges theory and application by integrating algorithmic strategies with case studies on predictive maintenance, renewable energy optimization, cyclone detection, heart disease prediction, and postpartum mental health risk assessment. It also investigates the role of circular economy principles in inventory optimization and examines future trends including neuromorphic computing and ethical AI.Key Features: Systematic exploration of AI-based optimization in mathematical modeling. In-depth coverage of ML/DL methods, quantum algorithms, and nature-inspired techniques. Practical applications in industrial manufacturing, healthcare, smart energy, and environmental resilience. Detailed discussions on model training, generalization, hyperparameter tuning, and overfitting control. Includes practical tools such as AutoML, PINNs, CNNs, and quantum convolutional networks. Forward-looking insights into sustainable optimization, interpretability, and autonomous AI systems.This volume is an essential resource for graduate students, researchers, and practitioners in applied mathematics, computer science, engineering, and data-driven optimization, offering the theoretical depth and application-driven clarity needed to tackle modern scientific and engineering challenges through AI-powered modeling and decision systems. Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between artificial intelligence and mathematical modeling. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 178,71
Envío por EUR 42,95Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between artificial intelligence and mathematical modeling. This edited volume brings together innovative research exploring how AI-driven methods re…volutionize traditional approaches to complex optimization problems, enabling enhanced performance, interpretability, and real-world applicability across diverse domains.Covering foundational and advanced topics, the book introduces readers to machine learning, deep learning, and reinforcement learning as critical tools for modeling high-dimensional, nonlinear, and stochastic systems. Chapters delve into essential aspects like data pre-processing, feature engineering, neural network architectures, swarm intelligence, quantum optimization, and multi-objective decision-making. Emerging techniques such as Fire Hawk Optimization Plus (FHO+), hybrid deep learning-quantum frameworks, and explainable AI (XAI) are discussed in the context of real-world scenarios ranging from energy systems and manufacturing to disaster prediction and healthcare analytics.This volume uniquely bridges theory and application by integrating algorithmic strategies with case studies on predictive maintenance, renewable energy optimization, cyclone detection, heart disease prediction, and postpartum mental health risk assessment. It also investigates the role of circular economy principles in inventory optimization and examines future trends including neuromorphic computing and ethical AI.Key Features: Systematic exploration of AI-based optimization in mathematical modeling. In-depth coverage of ML/DL methods, quantum algorithms, and nature-inspired techniques. Practical applications in industrial manufacturing, healthcare, smart energy, and environmental resilience. Detailed discussions on model training, generalization, hyperparameter tuning, and overfitting control. Includes practical tools such as AutoML, PINNs, CNNs, and quantum convolutional networks. Forward-looking insights into sustainable optimization, interpretability, and autonomous AI systems.This volume is an essential resource for graduate students, researchers, and practitioners in applied mathematics, computer science, engineering, and data-driven optimization, offering the theoretical depth and application-driven clarity needed to tackle modern scientific and engineering challenges through AI-powered modeling and decision systems. Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between artificial intelligence and mathematical modeling. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 251,19
Envío por EUR 6,81Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 262,61
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HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 325,05
Envío por EUR 32,57Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between artificial intelligence and mathematical modeling. This edited volume brings together innovative research exploring how AI-driven methods re…volutionize traditional approaches to complex optimization problems, enabling enhanced performance, interpretability, and real-world applicability across diverse domains.Covering foundational and advanced topics, the book introduces readers to machine learning, deep learning, and reinforcement learning as critical tools for modeling high-dimensional, nonlinear, and stochastic systems. Chapters delve into essential aspects like data pre-processing, feature engineering, neural network architectures, swarm intelligence, quantum optimization, and multi-objective decision-making. Emerging techniques such as Fire Hawk Optimization Plus (FHO+), hybrid deep learning-quantum frameworks, and explainable AI (XAI) are discussed in the context of real-world scenarios ranging from energy systems and manufacturing to disaster prediction and healthcare analytics.This volume uniquely bridges theory and application by integrating algorithmic strategies with case studies on predictive maintenance, renewable energy optimization, cyclone detection, heart disease prediction, and postpartum mental health risk assessment. It also investigates the role of circular economy principles in inventory optimization and examines future trends including neuromorphic computing and ethical AI.Key Features: Systematic exploration of AI-based optimization in mathematical modeling. In-depth coverage of ML/DL methods, quantum algorithms, and nature-inspired techniques. Practical applications in industrial manufacturing, healthcare, smart energy, and environmental resilience. Detailed discussions on model training, generalization, hyperparameter tuning, and overfitting control. Includes practical tools such as AutoML, PINNs, CNNs, and quantum convolutional networks. Forward-looking insights into sustainable optimization, interpretability, and autonomous AI systems.This volume is an essential resource for graduate students, researchers, and practitioners in applied mathematics, computer science, engineering, and data-driven optimization, offering the theoretical depth and application-driven clarity needed to tackle modern scientific and engineering challenges through AI-powered modeling and decision systems. Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between artificial intelligence and mathematical modeling. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
