開源的e-learning系統。Java環境，B/S結構。
標簽： e-learning Java 開源
上傳時間： 2013-12-25
上傳用戶：xfbs821
E learning and it s improvments
標簽： improvments learning and it
上傳時間： 2017-09-13
上傳用戶：璇珠官人
Agent技術的研究起源于人工智能領域。由于Agent具有自治性、智能性、反應性、主動性等優點，因此越來越受到人們的重視，并被廣泛應用于網絡技術和分布式計算。Agent技術很好的解決了網絡間任務分配及合作的問題，但Agent系統實際應用時的安全問題一直沒有得到很好的解決。本文設計了一個可實際應用的Mobile Agent系統安全問題解決方案，該方案可以有效解決實際運行中Agent系統的安全認證及安全通信問題。最后介紹了該方案在個性化e-learning系統中的實際應用情況。
上傳時間： 2014-01-26
上傳用戶：ztj182002
What you always wanted to know about networking but were afraid to ask! * How the Internet works * How e-mail, e-learning, and telephony work on the Internet * What makes a network safe * How traffic gets from here to there * Disaster recovery and other ways to keep a network running * How businesses share data * See the world of Cisco networking with this illustrated guide s visual approach to learning * Useful for both novices and networking professionals * Covers a broad variety of internetworking topics-from e-mail to VPNs At last-an illustrated guide to the world of Cisco networking. Cisco Networking Simplified breaks down the complicated world of internetworking into easy-to-understand parts. Learn quickly and easily the fundamentals of a variety of topics, such as security, IP telephony, and quality of service, from the full-color diagrams and clear explanations found in Cisco Networking Simplified.
標簽： networking Internet always afraid
上傳時間： 2013-12-14
上傳用戶：520
Pascal Programs Printed in GENETIC ALGORITHMS IN SEARCH, OPTIMIZATION, AND MACHINE LEARNING by David E. Goldberg
標簽： OPTIMIZATION ALGORITHMS LEARNING Programs
上傳時間： 2015-04-19
上傳用戶：
Simple GA code (Pascal code from Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning.)
標簽： D. E. code Optimization
上傳時間： 2014-12-07
上傳用戶：wlcaption
基本遺傳學習分類系統 A Simple Classifier System based on Genetic Learning developed from the Pascal SCS code presented by David E.Goldberg
標簽： Classifier developed Learning Genetic
上傳時間： 2014-08-07
上傳用戶：txfyddz
mani: MANIfold learning demonstration GUI by Todd Wittman, Department of Mathematics, University of Minnesota E-mail wittman@math.umn.edu with comments & questions. MANI Website: httP://www.math.umn.edu/~wittman/mani/index.html Last Modified by GUIDE v2.5 10-Apr-2005 13:28:36 Methods obtained from various authors. (1) MDS -- Michael Lee (2) ISOMAP -- J. Tenenbaum, de Silva, & Langford (3) LLE -- Sam Roweis & Lawrence Saul (4) Hessian LLE -- D. Donoho & C. Grimes (5) Laplacian -- M. Belkin & P. Niyogi (6) Diffusion Map -- R. Coifman & S. Lafon (7) LTSA -- Zhenyue Zhang & Hongyuan Zha
標簽： demonstration Mathematics Department University
上傳時間： 2016-10-29
上傳用戶：youmo81
Machine learning is about designing algorithms that automatically extract valuable information from data. The emphasis here is on “automatic”, i.e., machine learning is concerned about general-purpose methodologies that can be applied to many datasets, while producing something that is mean- ingful. There are three concepts that are at the core of machine learning: data, a model, and learning.
上傳時間： 2020-06-10
上傳用戶：shancjb
PCI-E電氣規格標準
上傳時間： 2013-05-26
上傳用戶：eeworm
