An Intelligent Database System To Support Administration Operations

Abstract

In this thesis an intelligent database system for computer components (IDSCCs) was developed as a powerful way of selecting compatible computer components or supporting managers decide which hardware component to invest in future. The developed system is built according to the following two branches; the first branch is active database systems (ADBSs) which are automatic monitoring of conditions defined over the database state and the ability to take actions when the state of the underlying database changes. Active databases can recognize specific situations (internal or external) and react to them without immediate, explicit user or application request. The other branch is neural networks which is one of the AI technology branches that simulates intelligence by attempting to reproduce the types of physical connections that occur in human brains. Prediction is one of the learning tasks that apply to the use of neural networks. The integration between those two technologies active database system (ADBSs) and neural networks (prediction techniques) leads to a powerful information system that can support the decision-making process. In these days, hardware parts, component pricing and building a PC from scratch is no longer the daunting process it once was. Every component necessary to build a PC is available on the shelf at competitive pricing. But, when planning to buy or upgrade a PC or investing in computer hardware components, two important things must be considered. First how all selected components will work together (hardware compatibility), second which computer component will be profitable for future to invest in money. Ensuring hardware compatibility or hardware profitability when building a system is a very complicated problem, which needs a great experience. This information of hardware compatibility and hardware profitability may be used as a database for the suggested intelligent database computer component system.