An artificial immune system algorithm, based on the Danger Theory, is an algorithm which emulates, in a computational context, the defense mechanism of the human immune system when presented with a danger to its wellbeing. Over its evolution the human immune system has developed a complex defense mechanism against entities which are harmful to the human body. This system is divided into two sub...

A spam detection model based on negative selection algorithm is proposed in this paper. The artificial immune system creates techniques to solve complex computations, aiming to developing immune based models. This is done by distinguishing self from non-self. Preliminary mathematical analysis will expose the computation and experimental description of the method and how it is applied to spam de...

Artificial Immune System is applied to determine the optimal hourly schedule of power generation in a hydrothermal system. A multi-reservoir cascaded hydroelectric system with a nonlinear relationship between water discharge rate, net head and power generation is considered. The water transport delay between connected reservoirs is taken into account. The transmission losses are also taken into...

An intelligent approach based on artificial immune systems (AIS) is proposed in this paper to perform the task of spectrum recognition in hyperspectral data analysis. Although traditional spectral matching techniques have provided some confirmatory information to aid the interpretation of hyperspectral data, the improvement is yet to be made because of the complexity of the spectra. The immunol...

The natural immune system is a robust and powerful information process system that demonstrates features such as distributed control, parallel processing and adaptation or learning via experience. Artificial Immune Systems (AIS) are machine-learning algorithms that embody some of the principles and attempt to take advantages of the benefits of natural immune systems for use in tackling complex ...

Computer security is an issue that will always be under investigation as intruders never stop to find ways to access data and network resources. Researches try to find functions and approaches that would increase chances to detect attacks and at the same time would be less expensive, regarding time and space. In this paper, an approach is applied to detect anomalous activity in the network, usi...

On the basis of analyzing immune learning mechanism, by modeling for image classification, we can solve the problem of remote sensing image classification by using the basic principles of the use of immune learning. We have realized a classification algorithm with a function of the immune learning. Classification algorithm divides each major category into a number of small categories and the an...

In this work, a system for solving handwritten Arabic word recognition is proposed. The aim is focused on holistic word recognition, which is devoted to recognize averaged size lexicons by using a single classifier. Presently, we investigate the applicability of the Artificial Immune Recognition System (AIRS) to achieve the recognition task. For the feature generation step, ridgelet transform a...

To keep the diversity of antibodies in artificial immune system evolution process, this paper puts forward a kind of increase simulation surname inheritance algorithm based on the clonal selection algorithm, and identification and forecast the Vibration Data about CA6140 horizontal lathe machining slender shaft workpiece prone. The results show that the algorithm has the characteristics of flex...

Fuzzy logic, neural network, fuzzy-neural networks play an important role in the linguistic modeling of intelligent control and decision making in complex systems. The Fuzzy-Neural Network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes an Artificial Immune Algorithm (AIA) based optimal learning fuzzy-neural network (IM-FNN). T...