Activation functions performance in multilayer perceptron for time series forecasting

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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...

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Bibliographic Details
Main Authors:	Nur Haizum, Abd Rahman, Yin, Chin Hui, Hani Syahida, Zulkafli
Format:	Conference or Workshop Item
Language:	English English
Published:	AIP Publishing 2024
Subjects:	QA Mathematics
Online Access:	http://umpir.ump.edu.my/id/eprint/42460/ 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

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