Water demand forecasting: review of soft computing methods
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DOI: 10.1007/s10661-017-6030-3
Abstract: Demand forecasting plays a vital role in resource management for governments and private companies. Considering the scarcity of water and its inherent constraints, demand management and forecasting in this domain are critically important. Several soft… read more here.
Keywords: water demand; soft computing; demand forecasting; computing methods ... See more keywords
A Comparison of Short-Term Water Demand Forecasting Models
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DOI: 10.1007/s11269-019-02213-y
Abstract: This paper presents a comparison of different short-term water demand forecasting models. The comparison regards six models that differ in terms of: forecasting technique, type of forecast (deterministic or probabilistic) and the amount of data… read more here.
Keywords: demand forecasting; water; term water; forecasting models ... See more keywords
A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting
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DOI: 10.1016/j.annals.2018.12.001
Abstract: This study reviews 211 key papers published between 1968 and 2018, for a better understanding of how the methods of tourism demand forecasting have evolved over time. The key findings, drawn from comparisons of method-performance… read more here.
Keywords: demand forecasting; tourism; annals tourism; tourism demand ... See more keywords
Density tourism demand forecasting revisited
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DOI: 10.1016/j.annals.2018.12.019
Abstract: Abstract This study used scoring rules to evaluate density forecasts generated by different time-series models. Based on quarterly tourist arrivals to Hong Kong from ten source markets, the empirical results suggest that density forecasts perform… read more here.
Keywords: demand forecasting; density forecasts; tourism; density ... See more keywords
Forecasting tourist arrivals using denoising and potential factors
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DOI: 10.1016/j.annals.2020.102943
Abstract: Abstract Precise tourist demand forecasting is crucial owing to its relevance in tourism decision-making. This study proposes a novel model for tourist demand forecasting on the basis of denoising and potential factors. The denoising strategy… read more here.
Keywords: tourist demand; denoising potential; potential factors; tourist ... See more keywords
Stochastic receding horizon control minimizing mean-variance with demand forecasting for home EMSs
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DOI: 10.1016/j.enbuild.2017.11.064
Abstract: Abstract As demand-side energy management system (EMS) has not only a function to maximize owner's utility by automatic control but also a potential capability to respond a demand activation, demand-side EMS is expected to fulfill… read more here.
Keywords: home; energy; control; receding horizon ... See more keywords
Peak demand alert system based on electricity demand forecasting for smart meter data
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DOI: 10.1016/j.enbuild.2020.110307
Abstract: Abstract Reducing peak demand is an important cost-saving measure for small and medium enterprises (SMEs) because electricity tariff menus often include a demand charge determined by the yearly highest demand. SMEs are incentivized to reduce… read more here.
Keywords: smart meter; peak demand; meter data; demand forecasting ... See more keywords
A Robust and Easy Approach for Demand Forecasting in Supply Chains
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DOI: 10.1016/j.ifacol.2018.08.206
Abstract: Abstract Demand forecasting plays an important role for supply chains decision making. It also represents a basis step for activity planning in response to customer demand. In this paper, recent advances in times series allow… read more here.
Keywords: robust easy; approach; supply chains; demand forecasting ... See more keywords
Daily retail demand forecasting using machine learning with emphasis on calendric special days
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DOI: 10.1016/j.ijforecast.2020.02.005
Abstract: Abstract Demand forecasting is an important task for retailers as it is required for various operational decisions. One key challenge is to forecast demand on special days that are subject to vastly different demand patterns… read more here.
Keywords: special days; machine learning; emphasis; demand forecasting ... See more keywords
An ensemble wavelet bootstrap machine learning approach to water demand forecasting: a case study in the city of Calgary, Canada
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DOI: 10.1080/1573062x.2015.1084011
Abstract: Abstract This paper explores a hybrid wavelet, bootstrap and neural network (WBNN) modeling approach for daily (1, 3 and 5 day) urban water demand forecasting in situations with limited data availability. This method was tested… read more here.
Keywords: wavelet bootstrap; water; demand forecasting; water demand ... See more keywords
An ensemble stacked model with bias correction for improved water demand forecasting
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DOI: 10.1080/1573062x.2020.1758164
Abstract: ABSTRACT Water demand forecasting is an essential task for water utilities, with increasing importance due to future societal and environmental changes. This paper suggests a new methodology for water demand forecasting, based on model stacking… read more here.
Keywords: demand forecasting; methodology; water; water demand ... See more keywords