This paper provides a non-systematic review of the progress of forecasting in social settings.
It is aimed at someone outside the field of forecasting who wants to understand and …

Demand forecasts are the lifeblood of supply chains. Academic literature and common
industry practices indicate that demand forecasts are often subject to human interventions …

With the advent of Big Data, nowadays in many applications databases containing large
quantities of similar time series are available. Forecasting time series in these domains with …

Public Policy Analysis, the most widely cited book on the subject, provides readers with a
comprehensive methodology of public policy analysis. Starting from the premise that policy …

Time series modeling and forecasting has fundamental importance to various practical
domains. Thus a lot of active research works is going on in this subject during several years …

Big data analytics and demand forecasting in supply chains: a conceptual analysis | Emerald
Insight Books and journals Case studies Expert Briefings Open Access Publish with us …

In order to accurately predict the short-term traffic flow, this paper presents a k-nearest
neighbor (KNN) model. Short-term urban expressway flow prediction system based on k-NN …

Purpose–This paper addresses a challenging topic, which in both academic and
professional literatures has been widely discussed but mainly from one single angle–that is …

Policy-and decision-makers in government and industry constantly face important decisions
without full knowledge of all the facts. They rely routinely on expert advice to fill critical …

This paper reports the results of the NN3 competition, which is a replication of the M3
competition with an extension of the competition towards neural network (NN) and …