Activation functions performance in multilayer perceptron for time series forecasting
Activation functions are important hyperparameters in neural networks, applied to calculate the weighted sum of inputs and biases and determine whether a neuron can be activated. Choosing the most suitable activation function can assist neural networks in training faster without sacrificing accuracy...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Jezik: | English English |
| Izdano: |
AIP Publishing
2024
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| Teme: | |
| Online dostop: | http://umpir.ump.edu.my/id/eprint/42460/1/2024%20Activation%20Functions%20Performance%20in%20Multilayer%20Perceptron%20for%20Time%20Series%20Forecasting.pdf http://umpir.ump.edu.my/id/eprint/42460/2/Activation%20functions%20performance%20in%20multilayer%20perceptron%20for%20time%20series%20forecasting.pdf |
Internet
http://umpir.ump.edu.my/id/eprint/42460/1/2024%20Activation%20Functions%20Performance%20in%20Multilayer%20Perceptron%20for%20Time%20Series%20Forecasting.pdfhttp://umpir.ump.edu.my/id/eprint/42460/2/Activation%20functions%20performance%20in%20multilayer%20perceptron%20for%20time%20series%20forecasting.pdf