Results 1 to 10 of about 27,738 (240)
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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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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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
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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
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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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Demand Forecasting of Spare Parts Using Artificial Intelligence: A Case Study of K-X Tanks
Mathematics, 2023 The proportion of the inventory range associated with spare parts is often considered in the industrial context. Therefore, even minor improvements in forecasting the demand for spare parts can lead to substantial cost savings.
Jae-Dong Kim +2 more
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Supply Chain Analytics, 2023 Forecasting demand and determining safety stocks are key aspects of supply chain planning. Demand forecasting involves predicting future demand for a product or service using historical data and other external and internal drivers.
Yasin Tadayonrad, Alassane Balle Ndiaye
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