Implementation of an Implicit Solver in ADCIRC Storm Surge Model

Alghamdi, Abdullah; Akbar, Muhammad

doi:10.3390/jmse6020062

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Air pollution is considered an environmental issue that affects human's health, whether in the long or short term. Around 7 million deaths per year are due to air pollution exposure and other atmospheric natural disasters [1]. The kingdom of Saudi Arabia is known for its desert environment.…”

Section: Introductionmentioning

confidence: 99%

Air Pollution Forecasting Using Deep Learning

et al. 2021

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Nowadays, air pollution is getting an extreme problem that affects the whole environment. Due to the dangerous effects of air pollution on human’s health, this study proposes an air pollution prediction system. Because of the high dust pollution in Saudi Arabia, and the fact that there is no system for predicting the percentage of air pollution in it, this study applies an air pollution prediction system to the most affected area in Saudi Arabia. This paper aims to forecast the concentrations of PM10 particles due to their dangerous effects. This study aims to align with the Saudi vision 2030 by having an ideal environment and act in an efficient way in case of a warning situation. It applies a deep learning technique, which called Long Short-Term Memory (LSTM) to predict the air pollution in Saudi Arabia and achieved exceptional results due to the low error rates that have been obtained by this study. The error rate of Mean Absolute Error (MAE) is 0.98, for Root Mean Square Error (RMSE) is 8.68 and 0.999 for R-Squared.

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Section: Introductionmentioning

confidence: 99%

Air Pollution Forecasting Using Deep Learning

et al. 2021

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“…The rea-son for the terminological differences is the lack of strong scientific traditions and practical experience in crisis management. The need for crisis management is determined by the objectives of the development of economic systems and the existence of the danger of a crisis (Archibald, 2010 andAlghamdi et al 2018). However, the ambiguity and diversity of the content of the crisis give different reasons for the classification of management in crisis situations (Boehm;Choetkiertikul et.al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Crisis Management Modeling of an Economic Object in Conditions Associated with Risks

Babenko

Бабій

Khelemskyi

et al. 2021

EEA

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The model of management of an economic object in a crisis is developed. Limitations and quality criteria are formed. General scheme of solving the task of minimax program crisis management at an enterprise is detected. The algorithm of the solution of the problem of crisis management of an enterprise taking into account the risks is offered. The main method for solving the problem is the method of detecting the reachable areas. Using this method, we work out the scenario of optimal crisis management in the presence of risks. The proposed algorithm allows to create effective numerous methods for implementing a computer simulation of solution of the problem of risk`s influencing. Simulated tools allow the reducing the risks at information system of crisis management of an enterprise. It opens the perspective of developing computer information systems for support of making effective crisis management decisions in the conditions of uncertainty and lack of information for increasing information security.

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Implementation of an Implicit Solver in ADCIRC Storm Surge Model

Cited by 2 publications

References 13 publications

Air Pollution Forecasting Using Deep Learning

Air Pollution Forecasting Using Deep Learning

Crisis Management Modeling of an Economic Object in Conditions Associated with Risks

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