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https://er.nau.edu.ua/handle/NAU/62256| Title: | Determination of Marketing Parameters for Building a Demand Forecasting Model using Neural Networks |
| Other Titles: | Визначення маркетингових параметрів для побудови моделі прогнозування попиту за допомогою нейронних мереж |
| Authors: | Sineglazov, Victor Синєглазов, Віктор Михайлович Novikov, Mikhaylo Новіков, Mихайло Сергійович |
| Keywords: | determination of marketing parameters forecasting neural networks regression models multilayer perceptron визначення маркетингових параметрів прогнозування нейронні мережі регресійні моделі багатошаровий персептрон |
| Issue Date: | 27-Dec-2023 |
| Publisher: | National Aviation University |
| Citation: | Sineglazov V. M. Determination of Marketing Parameters for Building a Demand Forecasting Model using Neural Networks / V. M. Sineglazov, M. S. Novikov // Electronics and Control Systems, N 4(78) – Kyiv: ТОВ «Альянт», 2023. – pp. 44–51 |
| Series/Report no.: | Electronics and Control Systems;№4(78) Електроніка та системи управління;№4(78) |
| Abstract: | This article is devoted to finding marketing parameters for building a demand forecasting model using neural networks using real data. The work deals with the problem of modeling product demand on the market in marketing using artificial intelligence and machine learning methods. The main features of existing approaches to building models of products on the market, their advantages and disadvantages are shown. The need for their improvement has been identified. A new methodology for solving the problem is presented. The model's demonstrated ability to predict consumer demand based on a variety of marketing parameters helps businesses plan inventory, production, and personnel more effectively and can lead to significant cost savings and improved efficiency. Cтаттю присвячено знаходженню маркетингових параметрів для побудови моделі прогнозування попиту за допомогою нейронних мереж з використанням реальних даних. У роботі розглянуто проблему в області моделювання попиту товару на ринку в маркетингу за допомогою методів штучного інтелекту та машинного навчання. Показано основні особливості існуючих підходів до побудови моделей товарів на ринку, їх переваги та недоліки. Виявлено потребу у їх вдосконаленні. Представлено нову методологію для розв’язання задачі. Продемонстровано здатність моделі успішно прогнозувати споживчий попит на основі різноманітних маркетингових параметрів, що допомагає підприємствам ефективніше планувати запаси, виробництво та персонал і може призвести до значної економії коштів та підвищенню ефективності. |
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| URI: | https://er.nau.edu.ua/handle/NAU/62256 |
| ISSN: | 1990-5548 |
| DOI: | 10.18372/1990-5548.78.18263 |
| Appears in Collections: | Наукові публікації та матеріали кафедри авіаційних комп'ютерно-інтегрованих комплексів (НОВА) |
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