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Mario Pérez-Gomariz, Antonio López-Gómez and Fernando Cerdán-Cartagena
The refrigeration industry is an energy-intensive sector. Increasing the efficiency of industrial refrigeration systems is crucial for reducing production costs and minimizing CO2 emissions. Optimization of refrigeration systems is often a complex and ti...
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Erich J. Plate and Khurram M. Shahzad
This paper demonstrates, by means of a systematic uncertainty analysis, that the use of outputs from more than one model can significantly improve conditional forecasts of discharges or water stages, provided the models are structurally different. Discha...
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Mirka Mobilia, Marius Schmidt and Antonia Longobardi
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Lan Wang, Mingjiang Xie, Min Pan, Feng He, Bing Yang, Zhigang Gong, Xuke Wu, Mingsheng Shang and Kun Shan
Harmful algal blooms (HABs) have been deteriorating global water bodies, and the accurate prediction of algal dynamics using the modelling method is a challenging research area. High-frequency monitoring and deep learning technology have opened up new ho...
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Khalid Alfalqi and Martine Bellaiche
Emergency events arise when a serious, unexpected, and often dangerous threat affects normal life. Hence, knowing what is occurring during and after emergency events is critical to mitigate the effect of the incident on humans? life, on the environment a...
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Mirka Mobilia and Antonia Longobardi
Evapotranspiration is the major component of the water cycle, so a correct estimate of this variable is fundamental. The purpose of the present research is to assess the monthly scale accuracy of six meteorological data-based models in the prediction of ...
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Waqas Ul Hussan, Muhammad Khurram Shahzad, Frank Seidel and Franz Nestmann
The accurate estimate of sediment load is important for management of the river ecosystem, designing of water infrastructures, and planning of reservoir operations. The direct measurement of sediment is the most credible method to estimate the sediments....
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Lin Chen, Chunying Ren, Lin Li, Yeqiao Wang, Bai Zhang, Zongming Wang and Linfeng Li
Accurate digital soil mapping (DSM) of soil organic carbon (SOC) is still a challenging subject because of its spatial variability and dependency. This study is aimed at comparing six typical methods in three types of DSM techniques for SOC mapping in an...
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Bahram Saeidifarzad, Vahid Nourani, Mohammad Taghi Aalami and Kwok-Wing Chau
Multi-site optimization of two adapted event-based geomorphologic rainfall-runoff models was presented using Non-dominated Sorting Genetic Algorithm (NSGA-II) method for the South Fork Eel River watershed, California. The first model was developed based ...
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Veronika Elisabeth Richter, Marc Syndicus, Jérôme Frisch and Christoph van Treeck
Future weather scenarios significantly affect indoor thermal comfort, influencing people?s well-being and productivity at work. Thus, future weather scenarios should be considered in the design phase to improve a building?s climate change resilience for ...
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Wei-Bo Chen and Wen-Cheng Liu
A large amount of accurate river cross-section data is indispensable for predicting river stages. However, the measured river cross-section data are usually sparse in the transverse direction at each cross-section as well as in the longitudinal direction...
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Wei-Bo Chen, Wen-Cheng Liu
Pág. 1 - 24
A large amount of accurate river cross-section data is indispensable for predicting river stages. However, the measured river cross-section data are usually sparse in the transverse direction at each cross-section as well as in the longitudinal direction...
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Yu Shen, Guineng Chen, Luís Miguel Martínez, João de Abreu e Silva
This paper presents a bi-level cellular agent-based model (ABM) framework, which incorporates a land cover change sub-model at the local level and a socioeconomic activity growth sub-model at the regional level. In the local sub-model, a land cell is set...
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Darin Majnaric, Sandi Baressi ?egota, Nikola Andelic and Jerolim Andric
One of the main problems in the application of machine learning techniques is the need for large amounts of data necessary to obtain a well-generalizing model. This is exacerbated for studies in which it is not possible to access large amounts of data?fo...
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Mukul Jaggi, Priyanka Mandal, Shreya Narang, Usman Naseem and Matloob Khushi
Stock price prediction can be made more efficient by considering the price fluctuations and understanding people?s sentiments. A limited number of models understand financial jargon or have labelled datasets concerning stock price change. To overcome thi...
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Meysam Nouri, Parveen Sihag, Farzin Salmasi and Ozgur Kisi
In this study, the energy dissipation of cascade spillways was studied by conducting a series of laboratory experiments. Five spillways slope angles (a) (10°, 20°, 30°, 40°, and 50°), various step numbers (N) ranging from 4 to 75, and a wide range of dis...
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Jinah Kim and Nammee Moon
Although various studies on monitoring dog behavior have been conducted, methods that can minimize or compensate data noise are required. This paper proposes multimodal data-based dog behavior recognition that fuses video and sensor data using a camera a...
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Jianguo Zheng, Yilin Wang, Shihan Li and Hancong Chen
Accurate stock market prediction models can provide investors with convenient tools to make better data-based decisions and judgments. Moreover, retail investors and institutional investors could reduce their investment risk by selecting the optimal stoc...
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Fiona Tulinayo,Theo van der Weide,Patrick van Bommel
Pág. 45 - 71
With the increasing need for data-based decision making, social systems and the ecosystems; practitioners and decision makers need guidance in their decision making, as is offered by data-based models and a systematic generation of simulation tools. Over...
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Hasan Omar Al-Sakran,Qasem Kharma,Irina Serguievskaia
Pág. pp. 10 - 15
Rapid spread of smart mobile technology that supports internet access is transforming the way governments provide services to their citizens. Mobile devices have different capabilities based on the manufacturers and models. This paper proposes a new fra...
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