1. What is an artificial neural network (ANN)?
An artificial neural network (ANN), often just called a "neural network" (NN), is a mathematical model or computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation.
2. How to create an ANN model for a problem domain?
ANN's are created using a knowledge base about the problem. It then goes through different calculations to determine the desired output for the problem. After the knowledge base has been learned by the Neural Network it can make better decisions for the problem. If the ANN continually learns from more input into the knowledge base it has the potential to make even better decisions and make more accurate decisions for the problem.
3. How does ANN compare with expert systems? How do they differ from each other as knowledge management tools?
ANN's are important tools when explicit knowledge cannot be defined as implicit knowledge. Many Expert Systems use implicit knowledge to find the answer to any given problem. An ANN has taken hold as a system that can infer answers to problems with little implicit knowledge based on the explicit knowledge that it has.
An artificial neural network (ANN), often just called a "neural network" (NN), is a mathematical model or computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation.
2. How to create an ANN model for a problem domain?
ANN's are created using a knowledge base about the problem. It then goes through different calculations to determine the desired output for the problem. After the knowledge base has been learned by the Neural Network it can make better decisions for the problem. If the ANN continually learns from more input into the knowledge base it has the potential to make even better decisions and make more accurate decisions for the problem.
3. How does ANN compare with expert systems? How do they differ from each other as knowledge management tools?
ANN's are important tools when explicit knowledge cannot be defined as implicit knowledge. Many Expert Systems use implicit knowledge to find the answer to any given problem. An ANN has taken hold as a system that can infer answers to problems with little implicit knowledge based on the explicit knowledge that it has.
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