Is Artificial Neural Network tough?
10 answers found
It is concluded that artificial neural networks have difficulty in returning consistently accurate answers under varying network conditions.
Artificial neural network is a versatile modelling tool capable of making predictions of values that are difficult to obtain in numerical analysis.
Among these, the artificial neural network (NN) system appears to be a powerful tool to tackle situations in w...
Due to its complexity, the artificial neural network must still be regarded as a more complicated technique.
The artificial neural network techniques are rather easy to develop and to perform.
Identification of three phase induction motor incipient faults using neural network
19 Sep 2004• 13 citations
Artificial neural network modeling is a logical choice to overcome these limitations.
Neural network approach to lumpy demand forecasting for spare parts in process industries
13 May 2008• 20 citations
It is observed that the inclusion of some more biological phenomenon in an artificial neural network can make it more powerful.
Time-series prediction with single integrate-and-fire neuron
01 Jun 2007• 17 citations
It can be concluded, from the results, that artificial neural network has the best performance with minimum mean square errors.
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.
State-of-the-art in artificial neural network applications: A survey
01 Nov 2018•Heliyon 481 citations
It was found that the optimal artificial neural network model is more accurate compared to the previous empirical correlation.
Why we study artificial neural network?10 answers