Natural Risk Management and Engineering NatRisk Project / [electronic resource] :
edited by Milan Gocić, Giuseppe Tito Aronica, Georgios E. Stavroulakis, Slaviša Trajković.
- 1st ed. 2020.
- VIII, 242 p. 100 illus., 79 illus. in color. online resource.
- Springer Tracts in Civil Engineering , 2366-2603 .
- Springer Tracts in Civil Engineering , .
Risk assessment tools and quality methods -- Model of effective civil-military collaboration in natural disaster risk management -- Natural disasters risk management in Bosnia and Herzegovina -- International trends in managing natural hazards and the role of leadership -- Natural disasters in industrial areas -- Contemporary approaches to natural disaster risk management in geotechnics -- Flood risk management modelling in the River Ibar catchment area -- Neuro fuzzy techniques and natural risk management -- A Discrete Inspired Bat Algorithm for Firetruck Dispatch in Emergency Situations -- Spatio-temporal distribution of hydrological and meteorological droughts in the South Morava basin.
This book summarizes the research being pursued as part of the Erasmus+ CBHE KA2 project entitled "Development of master curricula for natural disasters risk management in Western Balkan countries” (NatRisk), which aims to educate experts on the prevention and management of natural disasters in the Western Balkan region in line with national and EU policies. The project has successfully developed and implemented master curricula and educational training in the field of natural disasters risk management, and a methodology for the identification and prevention of natural disasters. Consisting of 11 chapters, the book analyzes and discusses topics such as risk assessment tools and quality methods, the different approaches for civil-military collaboration, natural disasters risk management in Bosnia and Herzegovina, leadership models for managing crises resulting from natural disasters, natural disasters in industrial areas, natural risk management in geotechnics, flood risk modeling, adaptive neuro-fuzzy inference models for flood prediction, collapse prediction of masonry arches, an algorithm for fire truck dispatch in emergency situations, and processing drought data in a GIS environment.