Bhardwaj Ramakant (90 results)

Condition: New. pp. 557 2nd Edition.

Paperback. Condition: Brand New. 68 pages. 8.66x5.94x0.39 inches. In Stock.

Soft cover. Condition: New. 1st Edition. The need for a textbook on Engineering Mathematics for Under Graduate students of Engineering as per the revised syllabus was felt by the UG students of Engineering. Taking into account the fact that there is no comprehensive text book for the Bachelor of Engineering students on Engineering Mathematics an attempt has been made to fill a niche that exists between more elementary books and books for advance studies. The book has been prepared according to the syllabus of various Technical Universities and is conceived as a text book for the course in Bachelor of Engineering of all branches. The contents of the book have been systematically organized and spread over fifteen chapters. The book not only covers the entire scope of the subject but explains the philosophy of the Basics of Engineering Mathematics, makes the understanding of the subject more interesting and explained with different types of solved examples. (jacket).…

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. In English.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Paperback. Condition: New. The book provides comprehensive and cognitive approach to building and deploying sophisticated information systems. The book utilizes non-linear optimization techniques, fuzzy logic, and rough sets to model various real-world use cases for the digital era. The hybrid information system modeling handles both qualitative and quantitative data and can effectively handle uncertainty and imprecision in the data. The combination of non-linear optimization mechanisms, fuzzy logic, and rough sets provides a robust foundation for next-generation information systems that can fulfill the demands of adaptive, aware, and adroit software applications for the knowledge era. The book emphasizes the importance of the hybrid approach, which combines the strengths of both mathematical and AI techniques, to achieve a more comprehensive and effective modeling process. Hybrid information system modeling techniques combine different approaches, such as fuzzy logic, rough sets, and neural networks, to create models that can handle the complexity and uncertainty of real-world problems. These techniques provide a powerful tool for modeling and analyzing complex systems, and the applications of hybrid information system modeling demonstrate their potential for solving real-world problems in various fields.…

Hardback. Condition: New. St ed.

Condition: New.

Condition: As New. Unread book in perfect condition.

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

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New. In English.

Condition: new.

Hardback. Condition: New. 2nd ND ed.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New.

Paperback. Condition: New. The book provides comprehensive and cognitive approach to building and deploying sophisticated information systems. The book utilizes non-linear optimization techniques, fuzzy logic, and rough sets to model various real-world use cases for the digital era. The hybrid information system modeling handles both qualitative and quantitative data and can effectively handle uncertainty and imprecision in the data. The combination of non-linear optimization mechanisms, fuzzy logic, and rough sets provides a robust foundation for next-generation information systems that can fulfill the demands of adaptive, aware, and adroit software applications for the knowledge era. The book emphasizes the importance of the hybrid approach, which combines the strengths of both mathematical and AI techniques, to achieve a more comprehensive and effective modeling process. Hybrid information system modeling techniques combine different approaches, such as fuzzy logic, rough sets, and neural networks, to create models that can handle the complexity and uncertainty of real-world problems. These techniques provide a powerful tool for modeling and analyzing complex systems, and the applications of hybrid information system modeling demonstrate their potential for solving real-world problems in various fields.…

Paperback. Condition: Brand New. 518 pages. 9.45x6.70x9.61 inches. In Stock.

Condition: New. 1st edition NO-PA16APR2015-KAP.