Tracked shipping to South Africa with premium packaging for just R199 

Ship to
South Africa
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Mathematical Foundations Of Nature-inspired Algorithms (springerbriefs In Optimization)
Type
Physical Book
Author
Publisher
Year
2019
Language
English
Pages
107
Format
Paperback
Dimensions
23.4 x 15.6 x 0.6 cm
Weight
0.18 kg.
ISBN13
9783030169350
Categories

Mathematical Foundations Of Nature-inspired Algorithms (springerbriefs In Optimization)

Xin-She Yang (Author) · Xing-Shi He (Author) · Springer · Paperback

Mathematical Foundations Of Nature-inspired Algorithms (springerbriefs In Optimization) - Yang, Xin-She ; He, Xing-Shi

Cheaper New Book Imported to South Africa
Delivery: 21 Jul - 18 Aug Shipping: 12 to 16 business days.
R 1,079
Faster New Book Imported to South Africa
Delivery: 09 Jul - 03 Aug Shipping: 4 to 5 business days.
R 1,306
R 1,079

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Mathematical Foundations Of Nature-inspired Algorithms (springerbriefs In Optimization)"

This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews