Forecast UPC-level FMCG demand, Part II: Hierarchical reconciliation

Yang, Di; Goh, Gary; Jiang, Siwei; Zhang, Allan N.; Akcan, Orkan

doi:10.1109/bigdata.2015.7363994

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…For instance, independent system operators (ISOs) have access to net generation data over a district, and PV system owners usually have string-level power production data. Utilizing information across a supply chain and revising forecasts made at various individual levels have shown economic and operational benefits in producing forecasts for fast-moving consumer goods (Yang et al, , 2015a, tourism (Hyndman et al, 2011;Athanasopoulos et al, 2009) and other operations management applications. It is important to consider information sharing in solar forecasting as well.…”

Section: University Of California San Diegomentioning

confidence: 99%

History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining

Yang¹,

Kleissl

Gueymard³

et al. 2018

Solar Energy

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404

164

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Text mining is an emerging topic that advances the review of academic literature. This paper presents a preliminary study on how to review solar irradiance and photovoltaic (PV) power forecasting (both topics combined as "solar forecasting" for short) using text mining, which serves as the first part of a forthcoming series of text mining applications in solar forecasting. This study contains three main contributions: (1) establishing the technological infrastructure (authors, journals & conferences, publications, and organizations) of solar forecasting via the top 1000 papers returned by a Google Scholar search; (2) consolidating the frequently-used abbreviations in solar forecasting by mining the full texts of 249 ScienceDirect publications; and (3) identifying key innovations in recent advances in solar forecasting (e.g., shadow camera, forecast reconciliation). As most of the steps involved in the above analysis are automated via an application programming interface, the presented method can be transferred to other solar engineering topics, or any other scientific domain, by means of changing the search word. The authors acknowledge that text mining, at its present stage, serves as a complement to, but not a replacement of, conventional review papers.

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Section: University Of California San Diegomentioning

confidence: 99%

History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining

Yang¹,

Kleissl

Gueymard³

et al. 2018

Solar Energy

Self Cite

404

164

View full text Add to dashboard Cite

show abstract

“…The concept of reconciliation emerges when the forecast quantity, such as renewable power generation [17][18][19], electrical load [20], tourism demand [21], or FMCG demand [22], can be modeled as a hierarchy. Due to the different information sets available at various levels in the hierarchy, e.g., retailers' business strategy is opaque to the distributor, and modeling uncertainties, the lower-level forecasts almost surely do not sum up to the higher-level forecasts.…”

Section: On Forecast Reconciliationmentioning

confidence: 99%

“…Experimental design, following Yang et al[22]. A total of N = 177 rolling forecasts are performed for each UPC time series.…”

mentioning

confidence: 99%

Impact of Information Sharing and Forecast Combination on Fast-Moving-Consumer-Goods Demand Forecast Accuracy

Yang

Zhang

2019

Information

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This article empirically demonstrates the impacts of truthfully sharing forecast information and using forecast combinations in a fast-moving-consumer-goods (FMCG) supply chain. Although it is known a priori that sharing information improves the overall efficiency of a supply chain, information such as pricing or promotional strategy is often kept proprietary for competitive reasons. In this regard, it is herein shown that simply sharing the retail-level forecasts—this does not reveal the exact business strategy, due to the effect of omni-channel sales—yields nearly all the benefits of sharing all pertinent information that influences FMCG demand. In addition, various forecast combination methods are used to further stabilize the forecasts, in situations where multiple forecasting models are used during operation. In other words, it is shown that combining forecasts is less risky than “betting” on any component model.

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Forecast UPC-level FMCG demand, Part I: Exploratory analysis and visualization

Yang

Goh

et al. 2015

2015 IEEE International Conference on Big Data (Big Data)

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Forecast UPC-level FMCG demand, Part II: Hierarchical reconciliation

Cited by 5 publications

References 19 publications

History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining

History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining

Impact of Information Sharing and Forecast Combination on Fast-Moving-Consumer-Goods Demand Forecast Accuracy

Forecast UPC-level FMCG demand, Part I: Exploratory analysis and visualization

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