Which branch of AI focuses on statistical models to solve problems with artificial neural network?
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| Papers (10) | Insight |
|---|---|
| An artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving complex problems. | |
1.4K Citations | The study found that neural-network models such as feedforward and feedback propagation artificial neural networks are performing better in its application to human problems. |
20 Citations | BACKGROUND Artificial neural networks (ANN) represent a promising alternative to classical statistical and mathematic methods to solve multidimensional nonlinear problems. |
| It is approved that artificial neural networks can be considerable effective in anticipating and analyzing flows in which traditional methods and statics are not able to solve. | |
17 Citations | Artificial neural networks (ANNs) offer promise for improving the predictive value of traditional statistical modeling. |
| The artificial neural network model shows lower errors and higher precision compared to statistical models while use of ANN is easier and quicker than statistical methods. | |
59 Citations | Artificial intelligence (AI) methods like artificial neural networks, genetic programming and genetic algorithms, and support vector machines are found to have better efficiency compared to statistical methods. |
87 Citations | Artificial neural networks represent a promising alternative to classical statistical and mathematical methods to solve multidimensional nonlinear problems. |
15 Citations | So, a practically convenient approach is to combine mathematical models of some aspects with artificial neural networks of those aspects which are difficult to measure or model. |
| By choosing one of the classes, an artificial neural network determines the problems that may arise in a given part of the water distribution system. |
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