8 Result(s)
within
Romulus Costache
Hydrogeology
-
Article
Open AccessFlood map** based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning
Among the various natural disasters that take place around the world, flood is considered to be the most extensive. There have been several floods in Buzău river basin, and as a result of this, the area has be...
-
Article
Open AccessPrediction of white spot disease susceptibility in shrimps using decision trees based machine learning models
Recently, the spread of white spot disease in shrimps has a major impact on the aquaculture activity worldwide affecting the economy of the countries, especially South-East Asian countries like Vietnam. This d...
-
Article
New Machine Learning Ensemble for Flood Susceptibility Estimation
Floods are among the most severe natural hazard phenomena that affect people around the world. Due to this fact, the identification of zones highly susceptible to floods became a very important activity in the...
-
Article
Quadratic Discriminant Analysis Based Ensemble Machine Learning Models for Groundwater Potential Modeling and Map**
In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning ensemble models, i.e., ABQDA, MBQD...
-
Article
Flood-prone area map** using machine learning techniques: a case study of Quang Binh province, Vietnam
Vietnam’s central coastal region is the most vulnerable and always at flood risk, severely affecting people’s livelihoods and socio-economic development. In particular, Quang Binh province is often affected by...
-
Article
Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Map**
Development of zoning and flood-forecasting models is essential for making optimal management decisions before and after floods. The Komijan watershed of Markazi Province, Iran is often affected by floods that...
-
Article
Potential of Hybrid Data-Intelligence Algorithms for Multi-Station Modelling of Rainfall
One of the most challenging tasks in rainfall prediction is designing a reliable computational methodology owing the random and stochastic characteristics of time-series. In this study, the potential of five d...
-
Article
Flood Susceptibility Assessment by Using Bivariate Statistics and Machine Learning Models - A Useful Tool for Flood Risk Management
In Romania, as in the rest of the world, the flood frequency has increased considerably. Prahova river basin is among the most exposed catchments of the country to flood risk. It also represents the area of th...
