Guest Editorial Everyday Applications Of Neural Networks

摘要

EURAL-NETWORK technology has reached a degree of maturity as evidenced by an ever-increasing number of applications. Our experience, however, is that most practitioners of neural networks are familiar with only a handful of cases where neural-network technology has been reduced to practice. The objective of this special issue is presentation of some specific cases of ongoing everyday use of neural networks. Specifically excluded are neural-network applications still in the exploratory stage. While publication of extraordinary exploratory applications papers is within the scope of the IEEE TRANSACTIONS ON NEURAL NETWORKS, this special issue deals only with neural networks used on a regular basis. At minimum, the system must be at the beta test stage. Of the 53 papers received for the special issue, the 14 herein were chosen. In some important cases, papers solicited for submission were unfortunately withheld because developers or licensees wished to not disclose proprietary technology. Nevertheless, the spectrum of the everyday neural-network applications reported herein is a veritable smorgasbord of variety. Applications are reported in telecommunications, control of Publisher Item Identifier S 1045-9227(97)05726-3. steel plants, plasma etching, pattern recognition of cataloged parts, credit card fraud detection, space robot tuning, electric utility load forecasting, railway maintenance, power system security assessment, scanning electron microscope image characterization, cold mill prediction, economic forecasting and, not least, assessment of wine bottle cork quality. This sampling of applications in everyday use is in no way complete. It gives, however, a taste of the impact of neural technology in society. Indeed, impact is the metric by which all technology is ultimately measured.