.png){kind=logo}
Stock image for illustration purposes only - book cover, edition or condition may vary.
Intelligent Data Engineering and Automated Learning -- IDEAL 2012
. Ed(S): Yin, Hujun; Costa, Jose A. F.; Barreto, Guilherme
€ 72.73
FREE Delivery in Ireland
Description for Intelligent Data Engineering and Automated Learning -- IDEAL 2012
Paperback. Editor(s): Yin, Hujun; Costa, Jose A. F.; Barreto, Guilherme. Series: Lecture Notes in Computer Science / Information Systems and Applications, Incl. Internet/Web, and HCI. Num Pages: 883 pages, 280 black & white illustrations, biography. BIC Classification: UMB; UNF; UNH; UYQ; UYQP; UYZG. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 44. Weight in Grams: 1217.
This book constitutes the refereed proceedings of the 13th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2012, held in Natal, Brazil, in August 2012. The 100 revised full papers presented were carefully reviewed and selected from more than 200 submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.
This book constitutes the refereed proceedings of the 13th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2012, held in Natal, Brazil, in August 2012. The 100 revised full papers presented were carefully reviewed and selected from more than 200 submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.
Product Details
Format
Paperback
Publication date
2012
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
883
Condition
New
Series
Lecture Notes in Computer Science / Information Systems and Applications, Incl. Internet/Web, and H
Number of Pages
862
Place of Publication
Berlin, Germany
ISBN
9783642326387
SKU
V9783642326387
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Intelligent Data Engineering and Automated Learning -- IDEAL 2012