Activation functions performance in multilayer perceptron for time series forecasting

• 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/42460/1/2024%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; http://umpir.ump.edu.my/id/eprint/42460/; https://doi.org/10.1063/5.0223864

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...