Bayesian forecasting in economics and finance: A modern review
The Bayesian statistical paradigm provides a principled and coherent approach to
probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting …
probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting …
A Review of Forecasting Studies for the Restaurant Industry: Focusing on results, contributions and limitations
Purpose: The purpose of this study is to explore restaurant forecasting studies through a
comprehensive review of existing studies, discuss the contributions and limitations of those …
comprehensive review of existing studies, discuss the contributions and limitations of those …
Introducing digital tools for sustainable food supply management: Tackling food loss and waste in industrial canteens
Reducing food waste is essential if we want to create a more sustainable food system, which
is why halving per capita food waste by 2030 has been included in the UN Sustainable …
is why halving per capita food waste by 2030 has been included in the UN Sustainable …
Avoiding food waste from restaurant tickets: a big data management tool
Purpose This study aims to address the global food waste problem in restaurants by
analyzing customer sales information provided by restaurant tickets to gain valuable insights …
analyzing customer sales information provided by restaurant tickets to gain valuable insights …
An empirical comparison of the sales forecasting performance for plastic tray manufacturing using missing data
The problem of missing data is frequently met in time series analysis. If not appropriately
addressed, it usually leads to failed modeling and distorted forecasting. To deal with high …
addressed, it usually leads to failed modeling and distorted forecasting. To deal with high …
[PDF][PDF] Food sales prediction model using machine learning techniques.
Food sales prediction means how to obtain future results of sales of companies. The
purpose of this step is to increase the profits of these companies by avoiding spoilage of …
purpose of this step is to increase the profits of these companies by avoiding spoilage of …
[HTML][HTML] Machine learning models for short-term demand forecasting in food catering services: A solution to reduce food waste
M Rodrigues, V Miguéis, S Freitas… - Journal of Cleaner …, 2024 - Elsevier
Food waste is responsible for severe environmental, social, and economic issues and
therefore it is imperative to prevent or at least minimize its generation. The main cause of …
therefore it is imperative to prevent or at least minimize its generation. The main cause of …
AWS IoT Core and Amazon DeepAR based predictive real-time monitoring framework for industrial induction heating systems
For embracing Industry 4.0 or the fourth industrial revolution, various industries are
implementing process automation and have started leveraging interconnectedness through …
implementing process automation and have started leveraging interconnectedness through …
Demand Forecasting for Food Production Using Machine Learning Algorithms: A Case Study of University Refectory
M Aci, D Yergök - Tehnički vjesnik, 2023 - hrcak.srce.hr
Sažetak Accurate food demand forecasting is one of the critical aspects of successfully
managing restaurants, cafeterias, canteens, and refectories. This paper aims to develop …
managing restaurants, cafeterias, canteens, and refectories. This paper aims to develop …
The Design of A Web-Based Inventory Management Application Using Predictive Modeling
JT Kusmana, NPK Rizaldi… - … Conference on Computer …, 2023 - ieeexplore.ieee.org
Stocks of raw materials are essential in food and beverage companies, but many companies
still cannot maintain stocks of raw materials in their inventory. This study aims to produce a …
still cannot maintain stocks of raw materials in their inventory. This study aims to produce a …