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Author 1
Rana Shakeel Ahmed
Lahore Leads University Pakistan
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Free Access | Research Article | 20 October 2024
Comparison of Deep Learning Algorithms for Retail Sales Forecasting
IECE Transactions on Intelligent Systematics | Volume 1, Issue 3: 112-126, 2024 | DOI:10.62762/TIS.2024.300700
Abstract
We investigate the use of deep learning models for retail sales predictions in this research. Having a proper sales forecasting can lead to optimization in inventory management, marketing strategies, and other core business operations. This research proposed to assess deep learning models such as Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Multilayer Perceptron and hybrid CNN-LSTM model. The models are further improved by using some dense layers to embed daily sales data from the biggest pharmaceutical firm in the study. Models are then trained on 80% of the dataset and tested on remaining 20%. The accuracy of the proposed research is compared using evaluation metrics... More >

Graphical Abstract
Comparison of Deep Learning Algorithms for Retail Sales Forecasting