A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting

NS Arunraj, D Ahrens - International Journal of Production Economics, 2015 - Elsevier
In the retail stage of a food supply chain, food waste and stock-outs occur mainly due to
inaccurate forecasting of sales which leads to incorrect ordering of products. The time series …

A methodology based on Deep Learning for advert value calculation in CPM, CPC and CPA networks

L Miralles-Pechuán, D Rosso, F Jiménez, JM Garcia - Soft Computing, 2017 - Springer
In this research, we propose a methodology for advert value calculation in CPM, CPC and
CPA networks. Accurately estimating this value increases the three previous networks' …

Oral-care goods sales forecasting using artificial neural network model

S Vhatkar, J Dias - Procedia computer science, 2016 - Elsevier
Supply Chain consists of various components like supplier, manufacturer, factories,
warehouses, distribution agents, customers, etc. Supply Chain Management encompasses …

Forecasting Infant Mortality Rate using Exponential Smoothing and Moving Averages Techniques

UY Madaki, UC Adamu, AA Muhammad… - Gadau Journal of Pure …, 2023 - gadaufos.com
Abstract Infant Mortality Rates (IMR) are important indicators of health status of any country.
This research presents Time Series Analysis using Exponential Smoothing and Moving …

Performance evaluation of ANN and neuro-fuzzy system in business forecasting

S Rajab, V Sharma - 2015 2nd international conference on …, 2015 - ieeexplore.ieee.org
In recent years, Artificial intelligence based algorithms are being widely used as prediction
models in different domains. However, the suitability and performance of a particular …

Comparison of Spatial Weight Matrices in Spatial Autoregressive Model: Case Study of Intangible Cultural Heritage in Indonesia

M Sobari, A Desiyanti, D Yanti, P Monika… - JTAM (Jurnal Teori …, 2023 - journal.ummat.ac.id
Abstract Intangible Cultural Heritage (ICH) can effectively contribute to Sustainable
Development Goals (SDGs) in all economic, social, and environmental dimensions, along …

Ensemble stock market prediction using svm, lstm, and linear regression

A Indika, N Warusamana, E Welikala, S Deegalla - Authorea Preprints, 2021 - techrxiv.org
Stock forecasting is challenging because of stock volatility and dependability on external
factors, such as economic, social, and political factors. This motivates investors to seek tools …

Design and Develop Data Analysis and Forecasting of the Sales Using Machine Learning

V Kadam, S Vhatkar - … Computing and Networking: Proceedings of IC-ICN …, 2022 - Springer
Abstract Data Analysis and Forecasting on Supermarket Sales Transactions is a proposed
system which focus on the betterment of the sales in the business. The whole proposed …

Check for updates Impact of Covid-19 Pandemic on Demand and Demand Forecasting in a Furniture Wholesale Company

R Al-Haidari, S Al-Rawashdeh, A Zeidan… - … Engineering in the …, 2024 - books.google.com
Accurate demand forecasting plays a critical role in most furniture businesses' operational,
tactical, and strategic decisions, as the demand in the furniture business is considered …

[PDF][PDF] Integrating artificial neural network with machine learning in forecasting problem domain

M Sahu - International Journal of Recent Research Aspects, 2015 - academia.edu
Fires in forest area is a major area of concern today because it is a major environmental
issue as well as creating economic and ecological damage and also endangering humans …