An automated method for costing flood risk mitigation measures for use with flood risk management decision support systems

2012 ◽  
Author(s):  
D Hames ◽  
M Woodward ◽  
B Gouldby
Keyword(s):  
Risk Management ◽  
Decision Support ◽  
Flood Risk ◽  
Support Systems ◽  
Risk Mitigation ◽  
Flood Risk Management ◽  
Mitigation Measures ◽  
Management Decision ◽  
Automated Method ◽  
Management Decision Support

scholarly journals Flood Risk Management Practices in Morocco: Facts and Challenges

2021 ◽  
pp. 35-94
Author(s):  
Dalila Loudyi ◽  
Moulay Driss Hasnaoui ◽  
Ahmed Fekri
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Flood Risk ◽  
Management Practices ◽  
Swot Analysis ◽  
Risk Mitigation ◽  
Integrated Management ◽  
Flood Risk Management ◽  
Mitigation Measures ◽  
The Government

AbstractFrom ancient flood management practices driven by agricultural activities to dam’s policy for water resources management including flood protection, to the National Strategy for Natural Disaster Risk Integrated Management; Morocco has come a long way in flood risk management. This chapter describes the recurrent flooding phenomenon plaguing the country along with progress in flood risk assessment approaches in terms of technique, governance, and best practices. An extensive number of research articles, administrative documents, consultancy, and international organizations reports are analyzed to give a holistic up-to-date insight into flood risk management in Morocco and present a comprehensive and critical view from a scientific perspective. Information and data were collected from a range of various sources and synthesized to integrate all scientific and governance aspects. Though analysis of this landscape shows progresses made by the Government to protect the population and reduce flood risk, it also shows shortcomings and challenges still to be overcome. Thus, a SWOT analysis was carried out for scoping and identifying the strengths, weaknesses, opportunities, and threats pertaining to this issue. The analysis reveals various success and failure factors related to three major components: governance, risk assessment approaches, and flood risk mitigation measures sustainability.

Review of classification studies for machine learning in the development of intelligent management decision support systems

2020 ◽  
Vol 89 ◽  
pp. 20-29
Author(s):  
Sh. K. Kadiev ◽  
◽  
R. Sh. Khabibulin ◽  
P. P. Godlevskiy ◽  
V. L. Semikov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Support ◽  
Mathematical Models ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Decision ◽  
Classification Methods ◽  
Advantages And Disadvantages ◽  
Intelligent Management ◽  
Management Decision Support

Introduction. An overview of research in the field of classification as a method of machine learning is given. Articles containing mathematical models and algorithms for classification were selected. The use of classification in intelligent management decision support systems in various subject areas is also relevant. Goal and objectives. The purpose of the study is to analyze papers on the classification as a machine learning method. To achieve the objective, it is necessary to solve the following tasks: 1) to identify the most used classification methods in machine learning; 2) to highlight the advantages and disadvantages of each of the selected methods; 3) to analyze the possibility of using classification methods in intelligent systems to support management decisions to solve issues of forecasting, prevention and elimination of emergencies. Methods. To obtain the results, general scientific and special methods of scientific knowledge were used - analysis, synthesis, generalization, as well as the classification method. Results and discussion thereof. According to the results of the analysis, studies with a mathematical formulation and the availability of software developments were identified. The issues of classification in the implementation of machine learning in the development of intelligent decision support systems are considered. Conclusion. The analysis revealed that enough algorithms were used to perform the classification while sorting the acquired knowledge within the subject area. The implementation of an accurate classification is one of the fundamental problems in the development of management decision support systems, including for fire and emergency prevention and response. Timely and effective decision by officials of operational shifts for the disaster management is also relevant. Key words: decision support, analysis, classification, machine learning, algorithm, mathematical models.

Sign in / Sign up

Export Citation Format

Share Document