Intelligent data engineering and automated learning -- IDEAL 2018 :
نام عام مواد
[Book]
ساير اطلاعات عنواني
19th International Conference, Madrid, Spain, November 21-23, 2018, Proceedings.
نام نخستين پديدآور
Hujun Yin, David Camacho, Paulo Novais, Antonio J. Tallón-Ballesteros (eds.).
مشخصه جلد
Part I /
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Cham, Switzerland :
نام ناشر، پخش کننده و غيره
Springer,
تاریخ نشرو بخش و غیره
2018.
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (xxvi, 865 pages) :
ساير جزييات
illustrations (some color)
فروست
عنوان فروست
Lecture notes in computer science ;
عنوان فروست
LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI
مشخصه جلد
11314
يادداشت کلی
متن يادداشت
Includes author index.
متن يادداشت
International conference proceedings.
یادداشتهای مربوط به مندرجات
متن يادداشت
Intelligent data analysis -- data mining and their associated learning systems and paradigms -- big data challenges -- machine learning, data mining, information retrieval and management -- bio- and neuro-informatics -- bio-inspired models including neural networks, evolutionary computation and swarm intelligence -- agents and hybrid intelligent systems, and real-world applications of intelligent techniques -- evolutionary algorithms -- deep learning neural networks -- probabilistic modeling -- particle swarm intelligence -- big data analytics and applications in image recognition -- regression, classification, clustering, medical and biological modelling and prediction -- text processing and social media analysis.
بدون عنوان
0
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
This two-volume set LNCS 11314 and 11315 constitutes the thoroughly refereed conference proceedings of the 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, held in Madrid, Spain, in November 2018. The 125 full papers presented were carefully reviewed and selected from 204 submissions. These papers provided a timely sample of the latest advances in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.