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Sabrina De Nardi, Claudio Carnevale, Sara Raccagni and Lucia Sangiorgi
Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-dr...
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Huei-Tau Ouyang, Shang-Shu Shih and Ching-Sen Wu
Inundation forecast models with non-sequential regressors are advantageous in efficiency due to their rather fewer input variables required to be processed. This type of model is nevertheless rare mainly because of the difficulty in finding the proper co...
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Huei-Tau Ouyang, Shang-Shu Shih, Ching-Sen Wu
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Inundation forecast models with non-sequential regressors are advantageous in efficiency due to their rather fewer input variables required to be processed. This type of model is nevertheless rare mainly because of the difficulty in finding the proper co...
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Taereem Kim, Ju-Young Shin, Hanbeen Kim, Sunghun Kim and Jun-Haeng Heo
Climate variability is strongly influencing hydrological processes under complex weather conditions, and it should be considered to forecast reservoir inflow for efficient dam operation strategies. Large-scale climate indices can provide potential inform...
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Silvia Golia, Luigi Grossi and Matteo Pelagatti
In this paper we assess how intra-day electricity prices can improve the prediction of zonal day-ahead wholesale electricity prices in Italy. We consider linear autoregressive models with exogenous variables (ARX) with and without interactions among pred...
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Cristina-Maria Stancioi, Iulia Adina ?tefan, Violeta Briciu, Vlad Mure?an, Iulia Clitan, Mihail Abrudean, Mihaela-Ligia Ungure?an, Radu Miron, Ecaterina Stativa, Michaela Nanu, Adriana Topan, Daniela Oana Toader and Ioana Nanu
The COVID-19 infectious disease spread in the world represents, by far, one of the most significant moments in humankind?s recent history, affecting daily activities for a long period of time. The data available now allow important modelling developments...
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Pei-Ching Chen and Kai-Yi Chien
In recent years, optimal control which minimizes a cost function formulated by weighted states and control inputs has been applied to the seismic control of structures. Optimal control requires structural states which may not be available in real applica...
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Kanishkavikram Purohit, Shivangi Srivastava, Varun Nookala, Vivek Joshi, Pritesh Shah, Ravi Sekhar, Satyam Panchal, Michael Fowler, Roydon Fraser, Manh-Kien Tran and Chris Shum
The proliferation of electric vehicle (EV) technology is an important step towards a more sustainable future. In the current work, two-layer feed-forward artificial neural-network-based machine learning is applied to design soft sensors to estimate the s...
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Shifei Yuan, Hongjie Wu and Chengliang Yin
State of charge (SOC) is a critical factor to guarantee that a battery system is operating in a safe and reliable manner. Many uncertainties and noises, such as fluctuating current, sensor measurement accuracy and bias, temperature effects, calibration e...
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