- document
-
Diab Montero, H.A. (author)In this dissertation, I explore ensemble data assimilation methods to enhance our capability to forecast earthquakes and slow slip events, focusing on the critical challenge posed by limited information on the current stress state of faults. <br/>At the outset, the research acknowledges the inherent limitations in our current understanding of...doctoral thesis 2024
- document
-
Li, G. (author), Knoop, V.L. (author), van Lint, J.W.C. (author)Traffic condition forecasting is fundamental for Intelligent Transportation Systems. Besides accuracy, many services require an estimate of uncertainty for each prediction. Uncertainty quantification must consider the inherent randomness in traffic dynamics, the so-called aleatoric uncertainty, and the additional distrust caused by data shortage...journal article 2024
- document
-
Marsman, C. P. (author), Vossepoel, F.C. (author), Van Dinther, Y. (author), Govers, R. (author)Bayesian-based data assimilation methods integrate observational data into geophysical forward models to obtain the temporal evolution of an improved state vector, including its uncertainties. We explore the potential of a variant, a particle method, to estimate mechanical parameters of the overriding plate during the interseismic period....journal article 2024
- document
-
Sadrtdinova, Renata (author), Perez, Gerald Augusto Corzo (author), Solomatine, D.P. (author)Kazakhstan is recently experiencing an increase in drought trends. However, low-capacity probabilistic drought forecasts and poor dissemination have led to a drought crisis in 2021 that resulted in the loss of thousands of livestock. To improve drought forecasting accuracy, this study applies Machine Learning and Deep Learning (ML and DL)...journal article 2024
- document
-
van der Drift, R. (author), de Haan, J. (author), Boelhouwer, P.J. (author)As housing development and housing market policies involve many long-term decisions, improving house price predictions could benefit the functioning of the housing market. Therefore, in this paper, we investigate how house price predictions can be improved. In particular, the merits of Bayesian estimation techniques in enhancing house price...journal article 2024
- document
-
Wang, X. (author), Corzo, Gerald (author), Lü, Haishen (author), Zhou, Shiliang (author), Mao, K. (author), Zhu, Yonghua (author), Duarte Prieto, F.S. (author), Liu, Mingwen (author), Su, Jianbin (author)Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compared to other climate system quantities, which makes it especially influential in shaping land...journal article 2024
- document
-
Raja, A.A. (author), Pinson, Pierre (author), Kazempour, Jalal (author), Grammatico, S. (author)In many areas of industry and society, including energy, healthcare, and logistics, agents collect vast amounts of data that are deemed proprietary. These data owners extract predictive information of varying quality and relevance from data depending on quantity, inherent information content, and their own technical expertise. Aggregating...journal article 2024
- document
-
Mateo-Barcos, S. (author), Ribo-Perez, D.G. (author), Rodríguez-García, J. (author), Alcázar-Ortega, M. (author)This study develops a methodology to characterise and forecast large consumers’ electricity demand, particularly municipalities, with hundreds of different metered supply points based on the previous characterisation of facilities’ consumption. Demand forecasting allows consumers to improve their participation in electricity markets and...journal article 2024
- document
-
de Bekker, Philippe (author), Cremers, S.A. (author), Norbu, Sonam (author), Flynn, David (author), Robu, Valentin (author)Given the fundamental role of renewable energy assets in achieving global temperature control targets, new energy management methods are required to efficiently match intermittent renewable generation and demand. Based on analysing various designed cases, this paper explores a number of heuristics for a smart battery scheduling algorithm that...journal article 2023
- document
-
Rahmani, S. (author), Baghbani, Asiye (author), Bouguila, Nizar (author), Patterson, Zachary (author)Graph neural networks (GNNs) have been extensively used in a wide variety of domains in recent years. Owing to their power in analyzing graph-structured data, they have become broadly popular in intelligent transportation systems (ITS) applications as well. Despite their widespread applications in different transportation domains, there is no...journal article 2023
- document
-
Muñoz, Paul (author), Corzo, Gerald (author), Solomatine, D.P. (author), Feyen, Jan (author), Célleri, Rolando (author)Extreme peak runoff forecasting is still a challenge in hydrology. In fact, the use of traditional physically-based models is limited by the lack of sufficient data and the complexity of the inner hydrological processes. Here, we employ a Machine Learning technique, the Random Forest (RF) together with a combination of Feature Engineering (FE...journal article 2023
- document
-
Oskina, M.I. (author), Farah, H. (author), Morsink, Peter (author), Happee, R. (author), van Arem, B. (author)The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a...journal article 2023
- document
-
Piadeh, Farzad (author), Behzadian, Kourosh (author), Chen, Albert S. (author), Kapelan, Z. (author), Rizzuto, Joseph P. (author), Campos, Luiza C. (author)This study presents a novel approach for urban flood forecasting in drainage systems using a dynamic ensemble-based data mining model which has yet to be utilised properly in this context. The proposed method incorporates an event identification technique and rainfall feature extraction to develop weak learner data mining models. These models...journal article 2023
- document
-
Vo, Tung (author), Barbour, N.M. (author), Palaio, Lori (author), Maness, Michael (author)Bikesharing is a popular transportation mode for people to commute, for leisurely travel, or for recreation purposes in their daily tasks. Throughout 2020, the COVID-19 pandemic had significant impacts on bikeshare usage in the United States. Previous studies show that the pandemic negatively affected bikeshare activity patterns. To examine the...book chapter 2023
- document
-
Umbrello, S. (author), Bernstein, Michael J. (author), Vermaas, P.E. (author), Resseguier, Anaïs (author), Gonzalez, Gustavo (author), Porcari, Andrea (author), Grinbaum, Alexei (author), Adomaitis, Laurynas (author)Various approaches have emerged over the last several decades to meet the challenges and complexities of anticipating and responding to the potential impacts of emerging technologies. Although many of the existing approaches share similarities, they each have shortfalls. This paper takes as the object of its study Anticipatory Ethics for...journal article 2023
- document
-
Piadeh, Farzad (author), Behzadian, Kourosh (author), Chen, Albert S. (author), Campos, Luiza C. (author), Rizzuto, Joseph P. (author), Kapelan, Z. (author)Urban flooding is a major problem for cities around the world, with significant socio-economic consequences. Conventional real-time flood forecasting models rely on continuous time-series data and often have limited accuracy, especially for longer lead times than 2 hrs. This study proposes a novel event-based decision support algorithm for...journal article 2023
- document
-
Vatandoust, Behzad (author), Zad, Bashir Bakhshideh (author), Vallée, François (author), Toubeau, Jean François (author), Bruninx, K. (author)Demand Response (DR) programs offer flexibility that is considered to hold significant potential for enhancing power system reliability and promoting the integration of renewable energy sources. Nevertheless, the distributed nature of DR resources presents challenges in developing scalable optimization tools. This paper explores a novel data...conference paper 2023
- document
-
Hinestroza Ramirez, Jhon Edinson (author), Soto Barbosa, Juan Ernesto (author), Yarce Botero, A. (author), Suárez Higuita, Danilo Andrés (author), Lopez-Restrepo, Santiago (author), Cruz Ruiz, Lisseth Milena (author), Sólorzano Araque, Valeria (author), Céspedes, Andres (author), Lorduy Hernandez, Sara (author)This manuscript introduces an exploratory case study of the SIMFAC’s (Sistema de Información Meteorológica de la Fuerza Aérea Colombiana) operational implementation of the Weather Research and Forecasting (WRF) model with a 3DVAR (three-dimensional variational) data assimilation scheme that provides meteorological information for military,...journal article 2023
- document
-
Zhang, Jinlei (author), Chen, Yijie (author), Krishnakumari, P.K. (author), Jin, Guangyin (author), Wang, Chengcheng (author), Yang, Lixing (author)Accurate and reliable short- term passenger flow prediction can support operations and decision-making of the URT system from multiple perspectives. In this paper, we propose a URT multi- step short- term passenger flow prediction model at the network level based on a Transformer-based LSTM network, Depth-wise Attention Block, and CNN network...journal article 2023
- document
-
Vohra, Rushil (author), Rajaei, A. (author), Cremer, Jochen (author)With the increasing penetration of renewable power sources such as wind and solar, accurate short-term, nowcasting renewable power prediction is becoming increasingly important. This paper investigates the multi-modal (MM) learning and end-to-end (E2E) learning for nowcasting renewable power as an intermediate to energy management systems. MM...conference paper 2023