Evolving connectionist systems (ECoSs) are a family of constructive artificial neural network
algorithms that were first proposed by Kasabov in 1998, where ldquoevolvingrdquo in this …

This paper proposes a novel hybrid algorithm for fault diagnosis of rotary kiln based on a
binary ant colony (BACO) and support vector machine (SVM). The algorithm can find a …

This paper presents a new kNN-based evolving neuro-fuzzy inference system (kENFIS). The
main function of kENFIS is to detect computer worms which possess a constant threat to …

Even if intrusion detection systems have marginally improved in the past few years, they still
face the problem of high false positives rate. In this paper we propose the use of a fuzzy …

With the growing rate of network attacks, intelligent methods for detecting new attacks have
attracted increasing interest. This paper presents an approach incorporating several soft …

In this paper, we introduce a new machine learning tool: a distributed autonomous neuro-
gen learning engine (DANGLE). The tool's motivation is to solve the lattice analysis of cubic …

For a long time neural networks have been a popular approach for intelligent machines
development and knowledge discovery. However, problems still exists in neural networks …

Intrusion detection technique has become increasingly important in the area of network
security research. It is innovative that various soft computing approaches have been applied …

Automating the detection of lesions in liver CT scans requires a high performance and
robust solution. With CT-scan start to become the norm in emergency department, the need …

An experimental gear-box was set-up to simulate the real situation of the wind-turbine.
Artificial cracks of different sizes were machined into the gear. Vibration signals were …