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{ "item_title" : "Computational Mathematics in Engineering", "item_author" : [" Praveen Kumar Gupta", "Subrata Bera", "Hiroyuki Ohshima "], "item_description" : "The monograph represents peer-reviewed original studies that make significant contributions to various branches of Computational Mathematics and Engineering. Each chapter highlights current trends in its respective research field and offers valuable insights, innovative methodologies, and recent advances in theories and computational applications. Key topics include artificial neural networks, data sciences, fuzzy set theory, numerical optimization techniques, soft computing, computational fluid dynamics and mathematical modelling. Additionally, several AI and machine learning algorithms are included, showcasing noteworthy computational results. This monograph features mathematical content validated by simulation results, enhancing the significance of the book. It serves as a valuable resource for both early-career and experienced researchers tackling complex real-world problems, such as addressing COVID-19 dynamics and solving transportation issues in engineering designs that traditional methods fail to resolve.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/11/914/566/3119145661_b.jpg", "price_data" : { "retail_price" : "186.99", "online_price" : "186.99", "our_price" : "186.99", "club_price" : "186.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Computational Mathematics in Engineering|Praveen Kumar Gupta

Computational Mathematics in Engineering : Proceedings of Iccma 2025

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Overview

The monograph represents peer-reviewed original studies that make significant contributions to various branches of Computational Mathematics and Engineering. Each chapter highlights current trends in its respective research field and offers valuable insights, innovative methodologies, and recent advances in theories and computational applications. Key topics include artificial neural networks, data sciences, fuzzy set theory, numerical optimization techniques, soft computing, computational fluid dynamics and mathematical modelling. Additionally, several AI and machine learning algorithms are included, showcasing noteworthy computational results. This monograph features mathematical content validated by simulation results, enhancing the significance of the book. It serves as a valuable resource for both early-career and experienced researchers tackling complex real-world problems, such as addressing COVID-19 dynamics and solving transportation issues in engineering designs that traditional methods fail to resolve.

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Details

  • ISBN-13: 9783119145664
  • ISBN-10: 3119145661
  • Publisher: de Gruyter
  • Publish Date: February 2026
  • Dimensions: 9.61 x 6.69 x 0.56 inches
  • Shipping Weight: 1.29 pounds
  • Page Count: 242

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