Furthermore, new threats are emerging such as cyber and cyber-physical threats, targeting the massive use of ICT in network management. Energy poverty remains an urgent issue in the EU.162 Indeed, smart grids seem to be an ideal response to this problem. Self-consumption directly combats ...
The presentation is conceptual in nature with emphasis on rationale, application, and interpretation of the most commonly used forecasting techniques. The goal of this book is to provide students and managers with an overview of a broad range of techniques and an understanding of the strengths and...
“There will be a shift from ‘supply chain management’ to ‘demand chain management,’” Adii predicts, adding that Cogsy is currently building a tool to give manufacturers more visibility and predictability in how the brand generates demand and sales. Product returns Free returnsare now consid...
Moreover, the development of time series forecasting techniques these years has witnessed a series of works employing time series forecasting techniques for practical applications such as bandwidth management14,15, resource allocation16, and resource provisioning17, where the time series prediction-based ...
wind speeds; most turbines are closer to 100 m above the ground. Nonetheless, these results indicate that GenCast provides more skilful wind forecasts that can capture joint spatial structure across real-world wind farm sites, indicating a potential value for the management and use of wind ...
Food demand forecasting models based on machine learning algorithms (such as the ones proposed in the present paper) have the potential to improve waste management in the HoReCa (Hotel, Restaurant, and Café) sector with their technological innovation (Martin-Rios et al., 2021), providing business...
New roads are being constructed all the time. However, the capabilities of previous deep forecasting models to generalize to new roads not seen in the trai
Critical discussions of trend extrapolatechniques, cross-impact matrices, substitution tion, “Delphi” theories, experience curves, and so on outline the uses and limitations of these tools. The major effort, however, is devoted to a model exercise in decision making, where the TF approach and ...
Following Fisher's work, four primary variants or supplementary approaches emerged as extensions to the single LSTM model: data decomposition, data dimension reduction, data augmentation techniques and Genetic Algorithm (GA) combination techniques. Primarily, in the realm of data decompositions, ...
Improved household-level forecasts may be useful to water managers in order to accurately identify, and potentially target for management and conservation, low-efficiency homes and relative high-demand customers. Advanced machine learning (ML) techniques are available for feature-based predictions, but ...