Modified Clonal Algorithm using Deep Learning

This article uses the basic frame work of Deep Learning Mechanism (DLM) to build a potential, versatile and robust classifier which can be applied to the diverse fields like bioinformatics, networks, image processing, compression and information retrieval. Detailed studies of various types of DLM and some classes of DLM referred as MADLM (Multiple Attractor DLM), GMADLM (General Multiple Attractor DLM) and FMADLM (Fuzzy Multiple Attractor DLM) were presented with their possible applications. This article concentrates in projecting MACA as a potential classification tool for specific applications in the domain of bioinformatics and network security

Additive Cellular Automata Augmented with Deep Learning for Pattern Reorganization

This article also a new approach to classify several problems based on the properties of Additive Cellular Automata. We use a state-transition which consists of a set of disjoint trees rooted at cyclic states of unit cycle length thus forming a natural classifier. The framework proposed is strengthened with genetic algorithm to find the desired local rule of the modeling as a global state function