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Michael Wood, Emanuele Ogliari, Alfredo Nespoli, Travis Simpkins and Sonia Leva
Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics and...
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Yanling Wu and Xiaoqin Yan
In this study, we investigate the changes in the multiyear predictability of the Pacific decadal oscillation (PDO) since 1900. A newly developed method, the model-analog method, is used to hindcast the PDO from 1900 to 2015. Model-analog hindcast provide...
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Georgios Venitourakis, Christoforos Vasilakis, Alexandros Tsagkaropoulos, Tzouma Amrou, Georgios Konstantoulakis, Panagiotis Golemis and Dionysios Reisis
Aiming at effectively improving photovoltaic (PV) park operation and the stability of the electricity grid, the current paper addresses the design and development of a novel system achieving the short-term irradiance forecasting for the PV park area, whi...
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Giuseppe Giunta, Alessandro Ceppi and Raffaele Salerno
Earth system predictions, from sub-seasonal to seasonal timescales, remain a challenging task, and the representation of predictability sources on seasonal timescales is a complex work. Nonetheless, advances in technology and science have been making con...
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Yiwen Li, Juan Liu, Pengfei Lin, Hailong Liu, Zipeng Yu, Weipeng Zheng and Jinlei Chen
Marine heatwaves (MHWs) are becoming increasingly frequent and intense around China, impacting marine ecosystems and coastal communities. Accurate forecasting of MHWs is crucial for their management and mitigation. In this study, we assess the forecastin...
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Han Wang, Ping-an Zhong, Ervin Zsoter, Christel Prudhomme, Florian Pappenberger and Bin Xu
Our paper aims to improve flood forecasting by establishing whether a global hydrological forecast system could be used as an alternative to a regional system, or whether it could provide additional information. This paper was based on the operational Gl...
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Fariborz Sobhanmanesh, Amin Beheshti, Nicholas Nouri, Natalia Monje Chapparo, Sandya Raj and Richard A. George
The widespread adoption of advanced technologies, such as Artificial Intelligence (AI), Machine Learning, and Robotics, is rapidly increasing across the globe. This accelerated pace of change is drastically transforming various aspects of our lives and w...
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Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing and Steven J. Schuldt
Organizations with large facility and infrastructure portfolios have used asset management databases for over ten years to collect and standardize asset condition data. Decision makers use these data to predict asset degradation and expected service life...
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Ying Li and Samuel N. Stechmann
Intuitively, one would expect a more skillful forecast if predicting weather averaged over one week instead of the weather averaged over one day, and similarly for different spatial averaging areas. However, there are few systematic studies of averaging ...
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Jozsef Pap, Csaba Mako, Miklos Illessy, Zef Dedaj, Sina Ardabili, Bernat Torok and Amir Mosavi
Given the importance of identifying key performance points in organizations, this research intends to determine the most critical intra- and extra-organizational elements in assessing the performance of firms using the European Company Survey (ECS) 2019 ...
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