The Arithmetic Optimization Algorithm based Forecasting System for Stock Prices

Stock price prediction and trading point prediction on are often used to adjust the weights of parameters in models to increase the accuracy of the models. This paper proposes a hybrid model based on the Arithmetic Optimization Algorithm (AOA), the Variational Modal Decomposition (VMD), and combines them with the long-short-term memory (LSTM) architecture to create a stock prediction system called Optimization of VMD using AOA based on LSTM (AVL). The experimental results show that the AVL performed better than the comparison models for predicting stock prices.

• Publication year

  2025

• Venue

  IEEE International Conference on Consumer Electronics

• Publication date

  2025-07-16

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICCE-Taiwan66881.2025.11207896
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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