Since the 1980's there have been renewed research efforts dedicated to neural networks. The present interest is largely due to the difficult problems confronted by artificial intelligence, and due to the deeper understanding of how the brain works, the recent developments in theoretical models, technologies and algorithms. One motivation of neural network research is the desire to build a new breed of powerful computers to solve a variety of problems that have proved to be very difficult with conventional computers. Another motivation is the desire to develop cognitive models that can serve as an alternative way to artificial intelligence. Human brain functions have not yet been successfully simulated in an AI system. Some existing neural network, on the other hand, have shown potential for these abilities. Using self-organization capabilities, neural networks are able to acquire and organize knowledge through learning in response to external stimuli. This paper addresses many techniques used in neural networks and possible applications in artificial intelligence. Some generic information about hybrid intelligent systems is also provided.
There have been a variety of neural network models developed by researchers of different backgrounds, from different point of view and with different aims and applications. However, neural networks are emulation of biological neural systems. With such an emulation it is hoped that some brain abilities, such as generalization, and attention focusing, can be simulated. The neural network can be defined in many ways. From the structural point of view, a neural network can be defined as a directed network (or graph) with ...
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...ithms can be integrated with neural networks to solve the complex problems in machine learning, such systems are called hybrid intelligent systems. Neural networks are very powerful tools for Intelligence Systems. Although there are some limitations in terms of the complexity of the neural circuit and the lack of representation in very complex systems, there is an ongoing research to improve performance and capabilities of neural networks.
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6. Neural Networks
7. Boltzmann Model
8. Kohonen Model
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