Possible Low-Priced, Robust Expert Systems Using Neural Networks and Minimal Entropy Coding

نویسنده

  • CHRISTIAN LIISBERG
چکیده

Within this paper the following research results are presented. A combination of minimal entropy coding and neural network technique is proposed for low-priced and robust expert system building A "thesis of tractability"' describing the size and complexity of ordinary human expertise when using the above-mentioned methods in knowledge engineering is given. Developmental and maintenance costs of expert and decision support systems can be cut down by more than 90 percent below the costs encountered when rule-based shells are used. A PC-based expert system shell (named ZEUS) incorporating the abovementioned principles has been developed, and two expert systems have been made. Both cases are tractable and significant cost reduction has been venfied in specific cases. Principles, techniques, and functionalities ofthe program ZEUS are described and evaluated.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust stability of stochastic fuzzy impulsive recurrent neural networks with\ time-varying delays

In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

متن کامل

Application of ANN Technique for Interconnected Power System Load Frequency Control (RESEARCH NOTE)

This paper describes an application of Artificial Neural Networks (ANN) to Load Frequency Control (LFC) of nonlinear power systems. Power systems, such as other industrial processes, have parametric uncertainties that for controller design had to take the uncertainties in to account. For this reason, in the design of LFC controller the idea of robust control theories are being used. To improve ...

متن کامل

Diagnosis of brain tumor using image processing and determination of its type with RVM neural networks

Typically, the diagnosis of a tumor is done through surgical sampling, which is more precise with existing methods. The difference is that this is an aggressive, time consuming and expensive way. In the statistical method, due to the complexity of the brain tissues and the similarity between the cancerous cells and the natural tissues, even a radiologist or an expert physician may also be in er...

متن کامل

A New Method for Detecting Ships in Low Size and Low Contrast Marine Images: Using Deep Stacked Extreme Learning Machines

Detecting ships in marine images is an essential problem in maritime surveillance systems. Although several types of deep neural networks have almost ubiquitously used for this purpose, but the performance of such networks greatly drops when they are exposed to low size and low contrast images which have been captured by passive monitoring systems. On the other hand factors such as sea waves, c...

متن کامل

Designing an expert system for differential diagnosis of β-Thalassemia minor and Iron-Deficiency anemia using neural network

Introduction: Artificial neural networks are a type of systems that use very complex technologies and non-algorithmic solutions for problem solving. These characteristics make them suitable for various medical applications. This study set out to investigate the application of artificial neural networks for differential diagnosis of thalassemia minor and iron-deficiency anemia. Methods: It is...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007