Displaying similar documents to “Intelligent prediction of milling strategy using neural networks”

Computer Networks Security Models - A New Approach for Denial-of-Services Attacks Mitigation

Tsvetanov, Tsvetomir (2010)

Serdica Journal of Computing

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Computer networks are a critical factor for the performance of a modern company. Managing networks is as important as managing any other aspect of the company’s performance and security. There are many tools and appliances for monitoring the traffic and analyzing the network flow security. They use different approaches and rely on a variety of characteristics of the network flows. Network researchers are still working on a common approach for security baselining that might enable early...

An Open Virtual World for Professional Development

Stefanova, Eliza (2013)

Serdica Journal of Computing

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The paper presents a study that focuses on the issue of sup-porting educational experts to choose the right combination of educational methodology and technology tools when designing training and learning programs. It is based on research in the field of adaptive intelligent e-learning systems. The object of study is the professional growth of teachers in technology and in particular that part of their qualification which is achieved by organizing targeted training of teachers. The article...

Evolutionary training for Dynamical Recurrent Neural Networks: an application in finantial time series prediction.

Miguel Delgado, M. Carmen Pegalajar, Manuel Pegalajar Cuéllar (2006)

Mathware and Soft Computing

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Theoretical and experimental studies have shown that traditional training algorithms for Dynamical Recurrent Neural Networks may suffer of local optima solutions, due to the error propagation across the recurrence. In the last years, many researchers have put forward different approaches to solve this problem, most of them being based on heuristic procedures. In this paper, the training capabilities of evolutionary techniques are studied, for Dynamical Recurrent Neural Networks. The...

Evolving co-adapted subcomponents in assembler encoding

Tomasz Praczyk (2007)

International Journal of Applied Mathematics and Computer Science

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The paper presents a new Artificial Neural Network (ANN) encoding method called Assembler Encoding (AE). It assumes that the ANN is encoded in the form of a program (Assembler Encoding Program, AEP) of a linear organization and of a structure similar to the structure of a simple assembler program. The task of the AEP is to create a Connectivity Matrix (CM) which can be transformed into the ANN of any architecture. To create AEPs, and in consequence ANNs, genetic algorithms (GAs) are...