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{ "item_title" : "Current Problems of Applied Mathematics and Computer Systems", "item_author" : [" Irina Samoylenko", "Anatoly Alikhanov", "Dmitrii Kaplun "], "item_description" : "This book based on the best papers accepted for presentation during the International Conference on Current Problems of Applied Mathematics and Computer Systems (CPAMCS-2024), Russia. This book includes research focused on contemporary mathematical challenges and their resolutions within scientific computing, data analysis and modular computing. This book presents original studies on numerical methods in scientific computing, optimization problem-solving, function approximation techniques, among other topics. Furthermore, it encompasses research contributions in data analysis and modular computing, highlighting advancements in deep learning, neural networks, mathematical statistics, machine learning techniques, residue number systems and artificial intelligence. Additionally, this book addresses critical issues in mathematical education. This book intends for professionals engaged in scientific computing, parallel computing, computer technology, machine learning, information security, and mathematics education. ", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/03/201/830/3032018307_b.jpg", "price_data" : { "retail_price" : "249.99", "online_price" : "249.99", "our_price" : "249.99", "club_price" : "249.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Current Problems of Applied Mathematics and Computer Systems|Irina Samoylenko

Current Problems of Applied Mathematics and Computer Systems : Cpamcs 2024

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Overview

This book based on the best papers accepted for presentation during the International Conference on Current Problems of Applied Mathematics and Computer Systems (CPAMCS-2024), Russia. This book includes research focused on contemporary mathematical challenges and their resolutions within scientific computing, data analysis and modular computing. This book presents original studies on numerical methods in scientific computing, optimization problem-solving, function approximation techniques, among other topics. Furthermore, it encompasses research contributions in data analysis and modular computing, highlighting advancements in deep learning, neural networks, mathematical statistics, machine learning techniques, residue number systems and artificial intelligence. Additionally, this book addresses critical issues in mathematical education. This book intends for professionals engaged in scientific computing, parallel computing, computer technology, machine learning, information security, and mathematics education.

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Details

  • ISBN-13: 9783032018304
  • ISBN-10: 3032018307
  • Publisher: Springer
  • Publish Date: October 2025
  • Dimensions: 9.21 x 6.14 x 1.19 inches
  • Shipping Weight: 2.04 pounds
  • Page Count: 522

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