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Více informací o knize Hybrid Soft Computing Techniques for Machine Learning and Optimization

• Parametry knihy
• Anotace
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Anotace knihy

Soft computing approaches, such as fuzzy logic, neural networks, and genetic algorithms, can be integrated into the realms of data analysis and decision making. They can be applied to tackle complex data analysis tasks and support decision-making processes in various domains, including healthcare, finance, manufacturing, and transportation. By extracting meaningful patterns, soft computing techniques may increase the effectiveness and efficiency in handling large datasets. In this way, they may be useful for facilitating decision making in uncertain and dynamic environments. Hybrid Soft Computing Techniques for Machine Learning and Optimization bridges the gap between theoretical knowledge and practical applications in soft computing and data analysis. It explores advancements and innovations in industries where data-driven decision making is crucial. Covering topics such as learning, biomedical signal processing, and entity behaviors, this book is an excellent resource for computer scientists, engineers, practitioners, healthcare professionals, finance professionals, manufacturers, transportation specialists, professionals, researchers scholars, academicians, and more.

Parametry knihy

Zařazení knihy Knihy v němčině Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Programmiersprachen

• Plný název: Hybrid Soft Computing Techniques for Machine Learning and Optimization
• Autor: Shruti Jain, Vinod Kumar Shukla
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 330
• EAN: 9798369368688
• ID: 48492199
• Nakladatelství: IGI Global
• Hmotnost: 572 g
• Rozměry: 254 × 178 × 18 mm
• Datum vydání: 18. April 2025

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