The Research Abstract Neural Networks and Artificial Intelligence Btech Seminar on Neural Networks and Artificial Intelligence talks about the human brain as an amazing processor. The research paper talks about the multiple challenges the human brain throws. The research abstract talks about the various applications that can be undertaken by Neural Networks not replacing the traditional standards of Artificial Intelligence. The paper talks about Neural Networks as an application used for processing large amounts of data. A considerable light is cast on Artificial Neural Networks as an emerging domain.
What is Artificial Neural Network : An artificial neural network is, in essence, an attempt to simulate the brain. Neural network theory revolves around the idea that certain key properties of biological neurons can be extracted and applied to simulations, thus creating a simulated (and very much simplified) brain. A neural network as defined Robert Hecht-Nielsen: “A neural network is a computing system which is made up of a number of simple, highly inter connected processing elements and which processes information by its dynamical state response to external inputs”.
Scope of Neural Networks:
Neural networks appear to be able to solve “monster” problems of AI that traditional systems have found difficulty with. These include , but are not limited to , speech recognition and synthesis , vision , and pattern recognition. Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques.
Advantages of Neural Networks:
- Adaptive learning: An ability to learn how to do tasks based on the data given for training or initial experience.
- Self-Organization: An ANN can create its own organization or representation of the information it receives during learning time.
- Real Time Operation: ANN computations may be carried out in parallel, and special hardware devices are being designed and manufactured which take advantage of this capability.
- Fault Tolerance via Redundant Information Coding: Partial destruction of a network leads to the corresponding degradation of performance. However, some network capabilities may be retained even with major network damage
The research abstract concludes positing that, artificial neural networks are one of the promises for the future in computing. They offer an ability to perform tasks outside the scope of traditional processors. Neural networks can now pick stocks , cull marketing prospects, approve loans, deny credit cards, tweak control systems, grade coins, and inspect work. Though neural networks have a huge potential we will only get the best of them when they are integrated with computing , AI , fuzzy logic and related subjects.
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