optimizationFSWTaguchigenetic algorithmmulti-objective optimizationThe artificial neural network (ANN) can be used as a model for friction stir welding (FSW), predicting the correlation between FSW parameters an
The cost function is a measure of how close the output of the neural network algorithm is to the expected output. The error backpropagation to minimize the cost is done using optimization algorithms such as stochastic gradient descent, batch gradient descent, or mini-batch gradient descent ...
The multilayer feed forward neural network with five inputs and one output has been trained with eight neurons in the hidden layer. A comparison of the experimental data with the dye adsorption efficiency predicted by the artificial neural network model showed that this model can estimate the ...
Because metamer generation relies on an iterative optimization procedure, it was important to measure optimization success. We considered the procedure to have succeeded only if it satisfied two conditions. First, measures of the match between the activations for the natural reference stimulus and its ...
Optimization is easy as compared to Sigmoid function. But still it suffers gradient vanishing problem. ReLu- Rectified Linear units It can be represented as: R(x) = max(0,x) if x < 0 , R(x) = 0 and if x >= 0 , R(x) = x ...
The advantages of e-commerce and information technology play an extremely important role in enhancing the competitiveness of the tourism industry and adapting to the needs of global economic integration. The development of e-commerce has played a huge ro
importance in recent years. Many papers in the literature have dealt with single faults but normally, more than one fault can occur in a rotor. This paper describes the application of artificial Neural Network (ANN) and Wavelet Transform (WT) for the prediction of the effect of combined ...
Fig. 5. Three-layer neural network. Layer 1 is input, layer 2 is “hidden layer,” and layer 3 is output. Arrows denote weights between neurons. A significant challenge to using ANN is finding the best weights without overfitting (20). The typical weight optimization method is to iterate ...
Building optimization involving multiple objectives is generally an extremely time-consuming process. The GAINN approach presented in this study first uses a simulation-based Artificial Neural Network (ANN) to characterize building behaviour, and then combines this ANN with a multiobjective Genetic Algorith...
1. The application of optimized artificial neural network to refraction static correction; 优化人工神经网络在折射波静校正中的应用更多例句>> 2) Designing and optimization ANN 人工神经网络优化设计3) evolutionary artificial neural network 进化人工神经网络...