Ganapathy Ganapathy Pattukandan

Centre for Disaster Mitigation and Management

Vellore Campus

Rajarathnam S.

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Arabian Journal of Geosciences

Several areas of Iran are prone to numerous natural hazards. An effective multi-hazard risk reduction requires analysis of the individual hazards and their interplay. This research develops a multi-hazard probability map for three hazards (i.e. landslides, floods, and earthquakes) for the management of hazard-prone areas in Lorestan Province, Iran, using anew ensemble model named SWARA-ANFIS-GWO. First, based on flood and landslide occurrence maps, hazard-prone areas were identified and sub-divided into two subsets.70% of these locations were randomly chosen to be used for the construction of susceptibility maps, while the remaining 30% of the instances were used to assess the accuracy of the models. Then, eleven factors relating to terrain and land use were selected for the preparation of landslide and flood susceptibility maps. An earthquake map was prepared based on a probabilistic seismic hazard analysis (PSHA). The SWARA method was implemented for weighting contributing factors and evaluating spatial relationships between the three hazards and predisposing factors. Subsequently, the ANFIS approach was used to acquire weights for each value while using a gray Wolf metaheuristic algorithm. Finally, all weight values were further assessed using the MATLAB software. The predicated results from the models were validated with ROC (rate of change) curves. The resulting AUCs (area under the curve) of the validation data indicated accuracies of 84% and 80% for floods and landslides, respectively, and 87% and 82.6%for flood and landslides based on the training data, respectively. Finally, the flood, landslide, and earthquake maps were combined to create a multi-hazard probability map of the Lorestan Province. This multi-hazard map serves as a valuable tool for land use planning and sustainable infrastructure development for the Lorestan Province. © 2019 Elsevier B.V.

Science of the Total Environment

Multi-hazard probability assessment and mapping in Iran

Natural Hazards

Probabilistic seismic hazard maps for the sultanate of Oman

Journal of Geophysics and Engineering

Extended deterministic seismic hazard assessment for the Aswan High Dam, Egypt, with emphasis on associated uncertainty

Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards

Probabilistic seismic hazard analysis for rock sites in the cities of Abu Dhabi, Dubai and Ra's Al Khaymah, United Arab Emirates

Bulletin of Earthquake Engineering

An evaluation of the applicability of the NGA models to ground-motion prediction in the Euro-Mediterranean region

Bulletin of the Seismological Society of America

Relationships between Median Values and between Aleatory Variabilities for Different Definitions of the Horizontal Component of Motion

Deterministic seismic hazard assessment for Sultanate of Oman

Journal	Data powered by TypesetArabian Journal of Geosciences
Publisher	Data powered by TypesetSpringer Science and Business Media LLC
ISSN	1866-7511
Open Access	Yes