Title

Database-driven Neural Networks and Evolutionary Computation

Abstract

More complex problems call for more complex solutions, but these solutions require either more programmers to encode, or more time. More programmers have more difficulty coordinating and end up wasting effort. Spending more time means waiting longer before reaping any benefits, and, if taken to the extreme, can completely prevent a project from being finished, as regular turnover replaces those working on it as fast as new programmers can be brought up to speed. When development time is valuable enough to sacrifice speed in the finished application, an entirely new set of programming languages becomes viable. In particular, a neural network can be cast as a pattern of database queries to a simple set of tables. This approach yields safer programs sooner, but the programs run rather slowly.

Department(s)

Electrical and Computer Engineering

Sponsor(s)

National Science Foundation (U.S.)

Keywords and Phrases

Evolutionary Computation; Neural Networks

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2003 American Society of Mechanical Engineers (ASME), All rights reserved.


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