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Predictive Modeling for Diaper Sales in Retail: An Artificial Neural Network Approach

Boma J. Luckyn Idayana Alabere O. A. E. Ogra

Subject area: Science,Engineering and Technology  ·  Area of research: Computer/Electronics Engineering

Abstract

The aim of this work is to determine the sale of diapers within the retail sector using the Artificial Neural Networks. The motivation for this study comes from the challenges that retailers have in managing inventory, improving customer satisfaction, and increasing profitability, all of which rely on accurate sales forecasting, a challenging problem when dealing with consumer commodities like diapers. Seasonality, promotional activity, and fluctuating customer preferences define the retail industry, emphasizing the importance of smart and adaptable forecasting methodologies. The work analyses and forecasts diaper sales using Artificial Neural Networks, which provide an adaptable framework for finding hidden trends in previous sales data, giving them a viable alternative to traditional forecasting methodologies. The work explores the distinctive problems and potential results presented by diaper sales projections, focusing on using Artificial Neural Networks to improve prediction precision and dependability. The work primary results include a thorough investigation of historical diaper sales data, a description of the neural network's architecture and training technique, and an evaluation of the model's performance on a dataset. These findings contribute not just to the wider topic of retail sales forecasting, but also provide useful information for retailers dealing with the complicated nature of diaper sales. The findings from the study are beneficial for strategic inventory management, operational efficiency, and overall decision-making processes in the retail industry, demonstrating how modern technologies such as Artificial Neural Networks have the potential to change how retailers respond to consumer requests in a competitive market scenario.

Keywords

Predictive Modeling, Diaper Sales, Retail, Artificial Neural Network (ANN)

References

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How to cite this paper

Boma J. Luckyn, Idayana Alabere, O. A. E. Ogra "Predictive Modeling for Diaper Sales in Retail: An Artificial Neural Network Approach" Iconic Research And Engineering Journals Volume 7 Issue 8 2024 Page 283-288
Boma J. Luckyn, Idayana Alabere, O. A. E. Ogra "Predictive Modeling for Diaper Sales in Retail: An Artificial Neural Network Approach" Iconic Research And Engineering Journals, vol. 7, no. 8, Feb. 2024
Boma J. Luckyn, Idayana Alabere, O. A. E. Ogra (2024). Predictive Modeling for Diaper Sales in Retail: An Artificial Neural Network Approach. Iconic Research And Engineering Journals, 7(8).
Boma J. Luckyn, Idayana Alabere, O. A. E. Ogra "Predictive Modeling for Diaper Sales in Retail: An Artificial Neural Network Approach" Iconic Research And Engineering Journals, vol. 7, no. 8, Feb. 2024.
@article{1705520,
      author = {Boma J. Luckyn, Idayana Alabere, O. A. E. Ogra},
      title = {Predictive Modeling for Diaper Sales in Retail: An Artificial Neural Network Approach},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {8},
      pages = {283-288},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17055201.pdf},
      abstract = {The aim of this work is to determine the sale of diapers within the retail sector using the Artificial Neural Networks. The motivation for this study comes from the challenges that retailers have in managing inventory, improving customer satisfaction, and increasing profitability, all of which rely on accurate sales forecasting, a challenging problem when dealing with consumer commodities like diapers. Seasonality, promotional activity, and fluctuating customer preferences define the retail industry, emphasizing the importance of smart and adaptable forecasting methodologies. The work analyses and forecasts diaper sales using Artificial Neural Networks, which provide an adaptable framework for finding hidden trends in previous sales data, giving them a viable alternative to traditional forecasting methodologies. The work explores the distinctive problems and potential results presented by diaper sales projections, focusing on using Artificial Neural Networks to improve prediction precision and dependability. The work primary results include a thorough investigation of historical diaper sales data, a description of the neural network's architecture and training technique, and an evaluation of the model's performance on a dataset. These findings contribute not just to the wider topic of retail sales forecasting, but also provide useful information for retailers dealing with the complicated nature of diaper sales. The findings from the study are beneficial for strategic inventory management, operational efficiency, and overall decision-making processes in the retail industry, demonstrating how modern technologies such as Artificial Neural Networks have the potential to change how retailers respond to consumer requests in a competitive market scenario.},
      keywords = {Predictive Modeling, Diaper Sales, Retail, Artificial Neural Network (ANN)},
      month = {February},
  }