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Self-Organizing Map in web mining Technical report

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بسم الله الرحمن الرحيم Self-Organizing Map Technical report Prepared by : Mogtapa Eltayip Abd-Elrhman Mohammed Index (12) Supervised: Abdelhamid Salih Ph.D Abstract Neural Networks are a computational approach which is based on a large collection of neural units loosely modeling the way the brain solves problems with large clusters of biological neurons connected by axons. Each neural unit is connected with many others, and links can be enforcing or inhibitory in their effect on the activation state of connected neural units INTRODUCTION The Self-Organizing Map is one of the most popular neural network models. It belongs to the category of competitive learning networks. The Self-Organizing Map is based on unsupervised learning, which means that no human intervention is needed during the learning and that little needs to be known about the characteristics of the input data. We could, for example, use the SOM for clustering data wit...
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Evolutionary computation

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Evolutionary computation Intelligence can be defined as the capability of a system to adapt its behavior to an ever-changing environment.  By modeling the process of evolution, we might expect to create intelligent behavior.  Evolutionary computation simulates evolution on a computer.  The result of such a simulation is a series of optimization algorithms, usually based on a simple set of rules.  Optimization improves the quality of solutions until an optimal, or at least feasible, solution is found. Is evolution really intelligent? We can consider the behavior of an individual organism as an inductive inference about some unknown aspects of its environment. Then if, over successive generations, the organism survives, we can say that this organism is capable of learning to predict changes in its environment.  The evolutionary approach to machine learning is based on computational models of natural selection and genetics. We call ...
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Artificial Intelligence Applications

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Particle Swarm Optimization Introduction  ·          Swarm Intelligence (SI) is an innovative distributed intelligent paradigm for solving optimization problems that originally took its inspiration from the biological examples by swarming, flocking.  ·          Particle Swarm Optimization (PSO) incorporates swarming behaviors observed in flocks of birds, schools of fish, or swarms of bees, and even human social behavior, from which the idea is emerged.  ·  ·          PSO is a population-based optimization tool, which could be implemented and applied easily to solve various function optimization problems, or the problems that can be transformed to function optimization problems. The flocking behavior of a group of birds   ·          As an algorithm, the main stre...
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Self-Organizing Map for Image Classification

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The Use of Self Organizing Map Method and Feature Selection in Image Classification System Introduction: Artificial Neural Network (ANN) is defined as an information processing system that has characteristics resembling human neural tissue. The existence of ANN provides a new technology to help solve problems that require thinking of experts and computer based routine. A few of ANN application was for classification system (clustering), association, pattern recognition, forecasting and analysis In this example the ANN method which applied is SOM method, that to be used to classify the image into a set of five different classes. In the Self Organizing Map (SOM) method, the applied learning is an unsupervised learning where the network does not utilize the class membership of sample training, but use the information in a group of neurons to modify the local parameter. The SOM system is adaptively classify samples (X image data) into classes deter...
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