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Rocío Escandón, Carmen María Calama-González, Alicia Alonso, Rafael Suárez and Ángel Luis León-Rodríguez
Climate change will have a great impact on the hottest climates of southern Europe and the existing residential stock will be extremely vulnerable to these future climatic conditions. Therefore, there is an urgent need to update this building stock consi...
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Mostafa Aliyari and Yonas Zewdu Ayele
This article aims to assess the effectiveness of state-of-the-art artificial neural network (ANN) models in time series analysis, specifically focusing on their application in prediction tasks of critical infrastructures (CIs). To accomplish this, shallo...
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Olga Petrucci and Roberto Coscarelli
In the future, as a result of global warming, it is possible that rainfall could become more intense and frequent. This could lead to more frequent triggering of damaging phenomena such as floods and landslides (named as a whole damaging hydrogeological ...
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Aristoteles Tegos, Nikolaos Malamos and Demetris Koutsoyiannis
Regional estimations of Potential Evapotranspiration (PET) are of key interest for a number of geosciences, particularly those that are water-related (hydrology, agrometeorology). Therefore, several models have been developed for the consistent quantific...
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Mihretab G. Tedla, Younghyun Cho and Kyungsoo Jun
In this study, we conducted flood mapping of a hypothetical dam break by coupling the Hydrologic Engineering Center?s Hydrologic Modeling System (HEC-HMS) and River Analysis System (HEC-RAS) models under different return periods of flood inflow. This stu...
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Shih-Chun Hsiao, Hongey Chen, Han-Lun Wu, Wei-Bo Chen, Chih-Hsin Chang, Wen-Dar Guo, Yung-Ming Chen and Lee-Yaw Lin
Super Typhoon Nepartak (2016) was used for this case study because it is the most intense typhoon that made landfall in Taiwan in the past decade. Winds extracted from the Climate Forecast System version 2 (CFSV2) and ERA5 datasets and merged with a para...
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Noriyuki Kushiro, Ami Fukuda, Masatada Kawatsu and Toshihiro Mega
In this study, methods for predicting energy demand on hourly consumption data are established for realizing an energy management system for buildings. The methods consist of an energy prediction algorithm that automatically separates the datasets to par...
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Emma L. Levin and Hiroyuki Murakami
Although anthropogenic climate change has contributed to warmer ocean temperatures that are seemingly more favorable for Atlantic hurricane development, no major hurricanes made landfall in the United States between 2006 and 2016. The U.S., therefore, ex...
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Radhakrishnan Angamuthu Chinnathambi, Anupam Mukherjee, Mitch Campion, Hossein Salehfar, Timothy M. Hansen, Jeremy Lin and Prakash Ranganathan
Forecasting hourly spot prices for real-time electricity markets is a key activity in economic and energy trading operations. This paper proposes a novel two-stage approach that uses a combination of Auto-Regressive Integrated Moving Average (ARIMA) with...
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Rana Muhammad Adnan, Zhongmin Liang, Xiaohui Yuan, Ozgur Kisi, Muhammad Akhlaq and Binquan Li
Accurate predictions of wind speed and wind energy are essential in renewable energy planning and management. This study was carried out to test the accuracy of two different neuro fuzzy techniques (neuro fuzzy system with grid partition (NF-GP) and neur...
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