SBIR Phase I: A Hybrid Neural Net Enterprise System Simulation

SBIR 第一阶段：混合神经网络企业系统模拟

• 批准号: 0232946
• 负责人: Robert Tarte
• 金额: $ 9.98万
• 依托单位: Pacific Code Works
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-01-01 至 2003-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0232946&HistoricalAwards=false
• 关键词: SBIR; Phase; Hybrid; Neural; Net

This Small Business Innovation Research Phase 1 project is designed to address the problem of managing and simulating extended enterprise systems as specified in The Extended Enterprise/C.2. As networks and enterprise systems have grown in complexity, it has become increasingly difficult to determine the most cost effective way to deploy hardware to maximize system availability and network performance. Poor resource planning decreases the effectiveness of information technology organizations, resulting in increased labor costs and decreased company wide productivity. New tools are required to increase productivity. This proposal is for research to produce a modeling and forecasting software system that use combination of neural net and rules based algorithms to simulate enterprise systems. Individual components of the enterprise system will be modeled with appropriate neural nets trained by constructive techniques. The enterprise system will be modeled by connecting these component neural nets with data pipe rule-based software. Such software would be able to forecast strains on the system and identify bottlenecks in the network. The completed modeling and forecasting software will become a cornerstone technology for a tool that will diagnose, troubleshoot and predict IT issues. The project will be developed in Linux with C, C++ or FORTRAN, as appropriate.This research could help in making the management of enterprise systems and networks more efficient therefore making them more affordable to teaching and service institutions.The result of this endeavor will assist enterprise systems and network managers to manage the tasks in faster and more economically manner.

这个小型企业创新研究第一阶段项目旨在解决管理和模拟扩展企业系统的问题，如扩展企业/C.2中规定的那样。随着网络和企业系统变得越来越复杂，确定部署硬件以最大化系统可用性和网络性能的最经济有效的方式变得越来越困难。不良的资源规划降低了信息技术组织的有效性，导致劳动力成本增加，并降低了整个公司的生产力。需要新工具来提高生产率。本课题旨在研究开发一种结合神经网络和基于规则的算法对企业系统进行仿真的建模和预测软件系统。企业系统的各个组成部分将通过构造技术训练的适当神经网络进行建模。将这些组件神经网络与基于数据管道规则的软件连接起来，对企业系统进行建模。这样的软件将能够预测系统的压力，并识别网络中的瓶颈。完成的建模和预测软件将成为诊断、排除故障和预测IT问题的工具的基础技术。该项目将酌情在Linux中使用C、c++或FORTRAN进行开发。这项研究有助于提高企业系统和网络的管理效率，从而使教学和服务机构更能负担得起。这一努力的结果将有助于企业系统和网络管理人员以更快、更经济的方式管理任务。