Big Data: Conceptual Analysis and Applications
暫譯: 大數據:概念分析與應用
Zgurovsky, Michael Z., Zaychenko, Yuriy P.
- 出版商: Springer
- 出版日期: 2019-03-29
- 售價: $5,640
- 貴賓價: 9.5 折 $5,358
- 語言: 英文
- 頁數: 277
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3030142973
- ISBN-13: 9783030142971
-
相關分類:
大數據 Big-data
海外代購書籍(需單獨結帳)
相關主題
商品描述
The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe-Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.
商品描述(中文翻譯)
本書專注於大數據的分析,以從這些數據中提取隱藏的模式,這些模式對於做出關於複雜系統理性行為的決策是必要的,這些系統具有生成這些數據的不同性質。為了解決這些問題,使用了一組基於計算過程自我組織的新方法和工具,包括清晰與模糊聚類分析方法、混合神經模糊網絡等。本書解決了各種實際問題。特別是在3D圖像識別和自動語音識別的任務中,使用了大規模神經網絡,並應用於深度學習系統。還介紹了混合神經模糊網絡在分析股市中的應用。對於大規模歷史、經濟和物理數據的分析揭示了隱藏的斐波那契模式,這與系統性世界衝突的進程及其與康德拉季耶夫大經濟周期和施瓦貝-沃爾夫太陽活動周期的關聯有關。本書對於在各種人類活動領域中與複雜系統打交道的系統分析師和實務工作者非常有用。