In this paper, some initial investigations are conducted to apply Artificial immune system(AIS) for classification of remotely sensed images. As a novel branch of computational intelligence, AIS has strong capabilities of pattern recognition, learning and associative memory, hence it is natural to view AIS as a powerful information processing and problem-solving paradigm in both the scientific ...

In order to further improve the ability of global path planning of coal mine rescue robot in the complex environment, a bacterial foraging algorithm-based polyclonal selection algorithm (BFA-PSA) is proposed. In order to verify the superiority of the BFA-PSA, the proposed algorithm is tested by traveling salesman problem (TSP) and compared with genetic algorithm (GA) and clonal selection algori...

The Clonal Selection Algorithm (CSA) is a widely used Artificial Immune Optimization (AIO) approach that tends to mimic the immune response when the pathogenic pattern is detected by the immune cells. However, this method, in its standard form, shows slow convergence and frequently traps in one of the local optima, especially for high dimensional problems. Hence, in this paper, an improved CSA ...

absTracT Many immue-inspired algorithms are based on the abstractions of one or several immunology theories, such as clonal selection, negative selection, positive selection, rather than the whole process of immune response to solve computational problems. In order to build a general computational framework by simulating immune response process, this chapter introduces a population-based artifi...

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Artificial Immune Systems inspired by clonal selection principle (called clonal selection algorithms) have already been successfully applied to pattern recognition tasks. In this paper we present our implementation of one of them, called CLONCLAS, and discuss its behavior in application to recognition of a set of binary patterns. The algorithm performs process of learning based on a set of trai...

This paper presents an experimental study on clonal selection algorithms (CSAs) to optimize simple and complex trap functions. Several settings of the proposed immune algorithms were tested in order to effectively face such a hard computational problem. The key feature to solve the trap functions, hence escape traps, is the usage of the hypermacromutation operator couple with a traditional pert...

This paper suggests novel hybrid optimization system (BF-CL) based on the bacterial foraging and clonal selection of immune system. A foraging strategy involves finding a patch of optimal condition (e.g., group of objective with conditions), deciding whether to enter it and search for optimal conditions, and when to leave the patch. There are predators and risks, energy required for optimizatio...

This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) technique...

Artificial immune systems (AIS) have become popular among researchers and have been applied to a variety of tasks. Developing supervised learning algorithms based on metaphors from the immune system is still an area in which there is much to explore. In this paper a novel supervised immune algorithm based on clonal selection framework is proposed. It evolves a population of linear classifiers u...