Recent drought and population growth are planting unprecedented demand for the use of available limited water resources. Irrigated agriculture is one of the major consumers of fresh water. Huge amount of water in irrigated agriculture is wasted due to poor water management practices. To improve water management in irrigated areas, models for estimation of future water requirements are needed. D...

decision trees as one of the data mining techniques, is used in credit scoring of bank customers. the main problem is the construction of decision trees in that they can classify customers optimally. this paper proposes an appropriate model based on genetic algorithm for credit scoring of banks customers in order to offer credit facilities to each class. genetic algorithm can help in credit sco...

Regional landslide susceptibility prediction (LSP) research is of great significance to the prevention and control landslides. This study focuses on LSP modelling based decision tree model. Taking northern part An’yuan County Jiangxi Province as an example, 14 environmental factors including elevation, gully density lithology are obtained geographical information system (GIS) remote sensing sat...

To estimate the compressive strength of cement-based materials with mining waste, dataset based on a series experimental studies was constructed. The support vector machine (SVM), decision tree (DT), and random forest (RF) models were developed compared. beetle antennae search (BAS) algorithm employed to tune hyperparameters learning models. predictive performances three compared by evaluation ...

Results of damage prediction in buildings can be used as a useful tool for managing and decreasing seismic risk of earthquakes. In this study, damage spectrum and C4.5 decision tree algorithm were utilized for damage prediction in steel buildings during earthquakes. In order to prepare the damage spectrum, steel buildings were modeled as a single-degree-of-freedom (SDOF) system and time-history...

Currently available methods for model selection used in phylogenetic analysis are based on an initial fixed-tree topology. Once a model is picked based on this topology, a rigorous search of the tree space is run under that model to find the maximum-likelihood estimate of the tree (topology and branch lengths) and the maximum-likelihood estimates of the model parameters. In this paper, we propo...

BACKGROUND In trauma patients, pancreatic injury is rare; however, if undiagnosed, it is associated with high morbidity and mortality rates. Few predictive models are available for the identification of pancreatic injury in trauma patients with elevated serum pancreatic enzymes. In this study, we aimed to construct a model for predicting pancreatic injury using a decision tree (DT) algorithm, a...

Word Sense Disambiguation (WSD) aims to disambiguate the words which have multiple sense in a context automatically. Sense denotes the meaning of a word and the words which have various meanings in a context are referred as ambiguous words. WSD is vital in many important Natural Language Processing tasks like MT, IR, TC, SP etc. This research paper attempts to propose a supervised Machine Learn...

The prediction of breast cancer recurrence is a crucial problem in research that requires accurate and efficient models. This study aims to compare the performance different machine learning techniques predicting types recurrence. In this study, logistic regression, decision tree, K-Nearest Neighbors, artificial neural network algorithms was compared on dataset. results show algorithm outperfor...

the prediction of liquefaction potential of soil due to an earthquake is an essential task in civil engineering. the decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. c4.5 is a known algorithm widely used to design decision trees. in this algorithm, a pruning process is carried out to solve the problem of the...