描述了MS SQL SERVER 7.0数据库系统中存储过程的基本概念以及存储过程的创建、调用和删除，介绍了各种语言环境（Delphi、ASP、PowerBuilder、VB）下存储过程的使用方法和步骤，并以一个具体应用展示了存储过程的编程特色以及使用上的...描述了MS SQL SERVER 7.0数据库系统中存储过程的基本概念以及存储过程的创建、调用和删除，介绍了各种语言环境（Delphi、ASP、PowerBuilder、VB）下存储过程的使用方法和步骤，并以一个具体应用展示了存储过程的编程特色以及使用上的灵活性和方便性，最后探讨了关于扩展存储过程缓冲区溢出漏洞问题以及存储过程的使用策略。展开更多
Based on the methods of fuzzy central clustering algorithms from unsupervised online recursive and offline learning methods, the limitation of initial sensitivity of clustering and learning of an objective function in...Based on the methods of fuzzy central clustering algorithms from unsupervised online recursive and offline learning methods, the limitation of initial sensitivity of clustering and learning of an objective function in constrained nonlinear optimum programming are analyzed. A modified offline learning approach is presented. The advantages and disadvantages of three kinds of fuzzy central clustering algorithms are compared by way of simulation. It shows that an approach proposed here not only decreases initial sensitivity of clustering but also accelerates termination learning of an objective function.展开更多
文摘描述了MS SQL SERVER 7.0数据库系统中存储过程的基本概念以及存储过程的创建、调用和删除，介绍了各种语言环境（Delphi、ASP、PowerBuilder、VB）下存储过程的使用方法和步骤，并以一个具体应用展示了存储过程的编程特色以及使用上的灵活性和方便性，最后探讨了关于扩展存储过程缓冲区溢出漏洞问题以及存储过程的使用策略。
文摘Based on the methods of fuzzy central clustering algorithms from unsupervised online recursive and offline learning methods, the limitation of initial sensitivity of clustering and learning of an objective function in constrained nonlinear optimum programming are analyzed. A modified offline learning approach is presented. The advantages and disadvantages of three kinds of fuzzy central clustering algorithms are compared by way of simulation. It shows that an approach proposed here not only decreases initial sensitivity of clustering but also accelerates termination learning of an objective function.
