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Zachary Patterson, Marko Kryvobokov, Fabrice Marchal, Michel Bierlaire
UrbanSim has significant data requirements. In particular, it requires disaggregate data (traditionally at the 150 meter by 150 meter gridcell level) for employment, households, and buildings. While such data are not always easily available, most regions...
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Yared Bayissa, Raghavan Srinivasan, George Joseph, Aroha Bahuguna, Anne Shrestha, Sophie Ayling, Ranjith Punyawardena and K. D. W. Nandalal
Developing an agricultural drought monitoring index through integrating multiple input variables into a single index is vital to facilitate the decision-making process. This study aims to develop an agricultural drought index (agCDI) to monitor and chara...
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Zhenwen He, Chunfeng Zhang, Xiaogang Ma and Gang Liu
Time series data are widely found in finance, health, environmental, social, mobile and other fields. A large amount of time series data has been produced due to the general use of smartphones, various sensors, RFID and other internet devices. How a time...
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Zhenwen He, Shirong Long, Xiaogang Ma and Hong Zhao
A large amount of time series data is being generated every day in a wide range of sensor application domains. The symbolic aggregate approximation (SAX) is a well-known time series representation method, which has a lower bound to Euclidean distance and...
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Yeran Sun, Yinming Ren and Xuan Sun
Recently, Uber released datasets named Uber Movement to the public in support of urban planning and transportation planning. To prevent user privacy issues, Uber aggregates car GPS traces into small areas. After aggregating car GPS traces into small area...
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Olivera Jovanovic, Jovan Zubovic, Marko Vladisavljevic, Du?ko Bodro?, Isidora Ljumovic, Ivana Domazet, Mihajlo Ðukic
Pág. 81 - 94
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Jing Liu, Xuesong Hai and Keqin Li
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their local data dir...
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Serio Agriesti, Claudio Roncoli and Bat-hen Nahmias-Biran
Agent-based modeling has the potential to deal with the ever-growing complexity of transport systems, including future disrupting mobility technologies and services, such as automated driving, Mobility as a Service, and micromobility. Although different ...
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Thomas C. Chiang and Yuanqing Zhang
This paper investigates the risk-return relations in Chinese equity markets. Based on a TARCH-M model, evidence shows that stock returns are positively correlated with predictable volatility, supporting the risk-return relation in both aggregate and sect...
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Thomas C. Chiang and Yuanqing Zhang
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Johannes Rude Jensen,Henrik Axelsen,Omri Ross
Pág. 92 - 103
Today, local financial institutions are responsible for submitting compliance reporting data to the supervisory authorities. This is commonly referred to as the ?push model?. The increasing complexity of reporting obligations often results in delayed rep...
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Zhenwen He, Chi Zhang and Yunhui Cheng
Time series data typically exhibit high dimensionality and complexity, necessitating the use of specific approximation methods to perform computations on the data. The currently employed compression methods suffer from varying degrees of feature loss, le...
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François Pinet
Data warehouses have demonstrated their applicability in numerous application fields such as agriculture, the environment and health. This paper proposes a general framework for defining a data warehouse and its aggregations using logic programming. The ...
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Jorge Amantegui, Hugo Morais and Lucas Pereira
Even though Industrial Kitchens (IKs) are among the highest energy intensity spaces, very little work has been done to forecast their consumption. This work explores the possibility of increasing the accuracy of the consumption forecast in an IK by forec...
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Maria-Evangelia Papadaki, Nicolas Spyratos and Yannis Tzitzikas
The continuous accumulation of multi-dimensional data and the development of Semantic Web and Linked Data published in the Resource Description Framework (RDF) bring new requirements for data analytics tools. Such tools should take into account the speci...
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Yufeng Yu, Dingsheng Wan, Qun Zhao and Huan Liu
Anomalous patterns are common phenomena in time series datasets. The presence of anomalous patterns in hydrological data may represent some anomalous hydrometeorological events that are significantly different from others and induce a bias in the decisio...
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Aliaksandr Kurachkin
Pág. 49 - 53
The paper proposes a unified declarative approach to developing and integrating medical information systems. Two main usage scenarios for data access are considered ? retrieving patient-based medical history for complex diagnostic scenarios, and retrievi...
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Odysseas Lamtzidis, Dennis Pettas and John Gialelis
Internet-of-Things (IoT) is an enabling technology for numerous initiatives worldwide such as manufacturing, smart cities, precision agriculture, and eHealth. The massive field data aggregation of distributed administered IoT devices allows new insights ...
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Quanbo Yuan, Huijuan Wang, Botao Wu, Yaodong Song and Hejia Wang
In order to achieve more efficient energy consumption, it is crucial that accurate detailed information is given on how power is consumed. Electricity details benefit both market utilities and also power consumers. Non-intrusive load monitoring (NILM), a...
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Xuantong Wang, Paul C. Sutton and Bingxin Qi
Frequent and rapid spatially explicit assessment of socioeconomic development is critical for achieving the Sustainable Development Goals (SDGs) at both national and global levels. Over the past decades, scientists have proposed many methods for estimati...
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