Gully erosion is a worldwide threat with numerous environmental, social, and economic impacts. The purpose of this research to evaluate the performance robustness six machine learning ensemble models based on decision tree principle: Random Forest (RF), C5.0, XGBoost, treebag, Gradient Boosting Machines (GBMs) Adaboost, in order map predict gully erosion-prone areas semi-arid mountain context. ...

Every year, malaria claims over a million lives around the globe. From which Ethiopia is a predominantly malaria prone country like most of sub Saharan African countries with about 75% of the landscape being favorable for the breeding of malaria vector and putting over 50 million people at risk. Attempts have been made to control the disease by eliminating the parasite. However, unknown spatial...

In order to understand the seismic performance and mechanism of bottom frame seismic wall masonry structure (BFSWMS) and its vulnerability in empirical seismic damage, based on the statistical and numerical analysis of the field seismic damage observation data of 2178 Dujiangyan structures in the Wenchuan great earthquake urban of China on May 12, 2008, a non-linear function model between the s...

Accurate information on the thermal preference and specialization of species is needed to understand and predict species geographical range size and vulnerability to climate change. Here we estimate the position and breadth of species within thermal gradients based on the shape of the response curve of species abundance to temperature. The objective of the study is to compare the measurements o...

the main objective of this study was to arak city zoning geomorphological parameters of the model using fuzzy logic. in order to realize these objectives, 10 parameters including of height, distance from fault, distance from the main channel, distance from sub-channel, distance from road, slope percent, distance from settlements, terrain type, erosion potential and seismic vulnerability in the ...