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A review of demand forecasting models and methodological developments within tourism and passenger transportation industry [PDF]
Journal of Tourism Futures, 2019 Purpose - The purpose of this paper is to review the current literature in the field of tourism demand forecasting. Design/methodology/approach - Published papers in the high quality journals are studied and categorized based their used forecasting ...
Iman Ghalehkhondabi +3 more
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An effective AI infused demand forecasting application for automotive spare parts industry: a real case from Turkey [PDF]
Scientific ReportsThe accuracy of demand forecasting in the automotive spare parts industry is critical to operational efficiency and financial performance. However, the irregular nature of spare parts demand makes forecasting processes quite complex.
Özge Albayrak Ünal +2 more
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An Insight of Deep Learning Based Demand Forecasting in Smart Grids [PDF]
Sensors, 2023 Smart grids are able to forecast customers’ consumption patterns, i.e., their energy demand, and consequently electricity can be transmitted after taking into account the expected demand.
Javier Manuel Aguiar-Pérez +1 more
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Research on China insurance demand forecasting: Based on mixed frequency data model. [PDF]
PLoS ONEIn this paper, we introduce the mixed-frequency data model (MIDAS) to China's insurance demand forecasting. We select the monthly indicators Consumer Confidence Index (CCI), China Economic Policy Uncertainty Index (EPU), Consumer Price Index (PPI), and ...
Cheng Wang +3 more
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Solar Radiation Forecasting Based on the Hybrid CNN-CatBoost Model
IEEE Access, 2023 The renewable energy industry is rapidly expanding due to environmental pollution from fossil fuels and continued price hikes. In particular, the solar energy sector accounts for about 48.7% of renewable energy, at the highest production ratio ...
Hyojeoung Kim +4 more
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Frontiers in Energy Research, 2022 Currently, traditional electricity consumers are now shifting to a new role of prosumers since more integration of renewable energy to demand side. Accurate short-term load demand forecasting is significant to safe, stable, and reliable operation of a ...
Jiying Wen +3 more
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Time Series Clustering of Electricity Demand for Industrial Areas on Smart Grid
Energies, 2020 This study forecasts electricity demand in a smart grid environment. We present a prediction method that uses a combination of forecasting values based on time-series clustering.
Heung-gu Son, Yunsun Kim, Sahm Kim
doaj +1 more source
Energy Reports, 2020 Machine learning approaches have diverse applications in forecasting electrical energy consumption using smart meter data. Various classification techniques and clustering methods analyze smart meter data for accurately forecasting the electrical ...
Ejaz Ul Haq +4 more
doaj +1 more source
Journal of Marine Science and Engineering, 2021 Demand forecasting has a pivotal role in making informed business decisions by predicting future sales using historical data. Traditionally, demand forecasting has been widely used in the management of production, staffing and warehousing for sales and ...
Ayesha Ubaid +2 more
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‘Horses for Courses’ in demand forecasting [PDF]
European Journal of Operational Research, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fotios Petropoulos +3 more
openaire +3 more sources