Isbn: 9798898814106 - experimental design of bio-inspired algorithms for optimization problems in industry 5.0: 1 (applied machine learning for iot and data analytics) (5 resultados)

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  • Idioma: Inglés

    Editorial: Bentham Science Publishers, 2026

    9798898814106

    Serie: Libro 1 de 5 - Applied Machine Learning for IoT and Data Analytics

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    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

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    EUR 119,08

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Bentham Science Publishers, 2026

    9798898814106

    Serie: Libro 1 de 5 - Applied Machine Learning for IoT and Data Analytics

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Bentham Science Publishers, 2026

    9798898814106

    Serie: Libro 1 de 5 - Applied Machine Learning for IoT and Data Analytics

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    Condición: New.

  • Idioma: Inglés

    Editorial: Bentham Science Publishers, 2026

    9798898814106

    Serie: Libro 1 de 5 - Applied Machine Learning for IoT and Data Analytics

    • Tapa blanda
    • Impresión bajo demanda

    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    EUR 119,07

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    Paperback. Condición: new. Paperback. Applied Machine Learning for IoT and Data Analytics (Volume 1) is an integrated exploration of nature-inspired optimisation techniques within the emerging Industry 5.0 paradigm- Positioned at the intersection of artificial intelligence, computational intelligence, industrial engineering, and cyber-physical systems, this volume centres on human-centricity, sustainability, resilience, and intelligent automation. The book comprehensively reviews evolutionary computation, swarm intelligence, neural computation, and hybrid metaheuristics, explaining how these methods can be systematically designed, statistically validated, and benchmarked for real-world deployment. Foundational chapters address Explainable AI (XAI), statistical experimental design, ANOVA-based modelling, parameter tuning strategies, and performance evaluation frameworks. Through fifteen carefully curated chapters, the book presents practical case studies in wireless sensor networks, smart manufacturing, micro-machining, welding optimisation, renewable energy systems, motor control, wireless communications, banking automation, and advanced antenna design. Emphasis is placed on experimental rigour, benchmarking, and reproducibility-bridging the gap between theoretical advancements and industrial implementation. Key Features: -Comprehensive review of classical and hybrid bio-inspired algorithms.-Integration of optimisation techniques within the Industry 5.0 framework.-Covers Explainable AI for transparent optimisation systems with a strong focus on experimental design, ANOVA modelling, and statistical validation.-Practical case studies across manufacturing, energy, communications, and automation.-Emphasis on reproducibility and methodological rigour with forward-looking insights into AI-enhanced and explainable optimisation trends. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Bentham Science Publishers, 2026

    9798898814106

    Serie: Libro 1 de 5 - Applied Machine Learning for IoT and Data Analytics

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    Condición: Nuevo

    EUR 119,67

    Envío por EUR 43,65 
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    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. Applied Machine Learning for IoT and Data Analytics (Volume 1) is an integrated exploration of nature-inspired optimisation techniques within the emerging Industry 5.0 paradigm- Positioned at the intersection of artificial intelligence, computational intelligence, industrial engineering, and cyber-physical systems, this volume centres on human-centricity, sustainability, resilience, and intelligent automation. The book comprehensively reviews evolutionary computation, swarm intelligence, neural computation, and hybrid metaheuristics, explaining how these methods can be systematically designed, statistically validated, and benchmarked for real-world deployment. Foundational chapters address Explainable AI (XAI), statistical experimental design, ANOVA-based modelling, parameter tuning strategies, and performance evaluation frameworks. Through fifteen carefully curated chapters, the book presents practical case studies in wireless sensor networks, smart manufacturing, micro-machining, welding optimisation, renewable energy systems, motor control, wireless communications, banking automation, and advanced antenna design. Emphasis is placed on experimental rigour, benchmarking, and reproducibility-bridging the gap between theoretical advancements and industrial implementation. Key Features: -Comprehensive review of classical and hybrid bio-inspired algorithms.-Integration of optimisation techniques within the Industry 5.0 framework.-Covers Explainable AI for transparent optimisation systems with a strong focus on experimental design, ANOVA modelling, and statistical validation.-Practical case studies across manufacturing, energy, communications, and automation.-Emphasis on reproducibility and methodological rigour with forward-looking insights into AI-enhanced and explainable optimisation trends. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…