Improving sporadic demand forecasting using a modified k-nearest neighbor framework
Forecasting sporadic or intermittent demand presents significant challenges in supply chain
management, primarily due to the frequent occurrence of zero demand values and the …
management, primarily due to the frequent occurrence of zero demand values and the …
Forecasting supply chain sporadic demand with nearest neighbor approaches
One of the biggest challenges in Supply Chain Management (SCM) is to forecast sporadic
demand. Our forecasting methods' arsenal includes Croston's method, SBA and TSB as well …
demand. Our forecasting methods' arsenal includes Croston's method, SBA and TSB as well …
Intermittent demand forecasts with neural networks
N Kourentzes - International Journal of Production Economics, 2013 - Elsevier
Intermittent demand appears when demand events occur only sporadically. Typically such
time series have few observations making intermittent demand forecasting challenging …
time series have few observations making intermittent demand forecasting challenging …
On intermittent demand model optimisation and selection
N Kourentzes - International Journal of Production Economics, 2014 - Elsevier
Intermittent demand time series involve items that are requested infrequently, resulting in
sporadic demand. Croston׳ s method and its variants have been proposed in the literature to …
sporadic demand. Croston׳ s method and its variants have been proposed in the literature to …
Forecasting of customer demands for production planning by local k-nearest neighbor models
Demand forecasting is of major importance for manufacturing companies since it provides a
basis for production planning. However, demand forecasting can be a difficult task because …
basis for production planning. However, demand forecasting can be a difficult task because …
Empirical heuristics for improving intermittent demand forecasting
F Petropoulos, K Nikolopoulos… - … Management & Data …, 2013 - emerald.com
Intermittent demand appears sporadically, with some time periods not even displaying any
demand at all. Even so, such patterns constitute considerable proportions of the total stock in …
demand at all. Even so, such patterns constitute considerable proportions of the total stock in …
Elucidate structure in intermittent demand series
N Kourentzes, G Athanasopoulos - European Journal of Operational …, 2021 - Elsevier
Intermittent demand forecasting has been widely researched in the context of spare parts
management. However, it is becoming increasingly relevant to many other areas, such as …
management. However, it is becoming increasingly relevant to many other areas, such as …
Intermittent demand forecasting with transformer neural networks
Intermittent demand forecasting is an important yet challenging task in many organizations.
While prior research has been focused on traditional methods such as Croston's method …
While prior research has been focused on traditional methods such as Croston's method …
[图书][B] Intermittent demand forecasting: Context, methods and applications
JE Boylan, AA Syntetos - 2021 - books.google.com
INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and
approaches of intermittent, rather than fast, demand forecasting Intermittent Demand …
approaches of intermittent, rather than fast, demand forecasting Intermittent Demand …
Forecasting spare parts sporadic demand using traditional methods and machine learning-a comparative study
B Adur Kannan, G Kodi, O Padilla, D Gray… - SMU Data Science …, 2020 - scholar.smu.edu
Sporadic demand presents a particular challenge to traditional time forecasting methods. In
the past 50 years, there has been developments, such as, the Croston Model [3], which has …
the past 50 years, there has been developments, such as, the Croston Model [3], which has …