Search results for " Machine learning techniques"

showing 2 items of 2 documents

Predicting sediment deposition rate in check-dams using machine learning techniques and high-resolution DEMs

2021

Sediments accumulated in check dams are a valuable measure to estimate soil erosion rates. Here, geographic information systems (GIS) and three machine learning techniques (MARS-multivariate adaptive regression splines, RF-random forest and SVM-support vector machine) were used, for the first time, to predict sediment deposition rate (SR) in check-dams located in six watersheds in SW Spain. There, 160 dry-stone check dams (~ 77.8 check-dams km−2), accumulated sediments during a period that varied from 11 to 23 years. The SR was estimated in former research using a topographical method and a high-resolution Digital Elevation Model (DEM) (average of 0.14 m3 ha−1 year−1). Nine environmental-to…

Mean squared error0208 environmental biotechnologyMean absolute errorSoil ScienceHigh resolution02 engineering and technology010501 environmental sciencesMachine learningcomputer.software_genre01 natural sciencesEnvironmental ChemistryDigital elevation model0105 earth and related environmental sciencesEarth-Surface ProcessesWater Science and TechnologyGlobal and Planetary ChangeMultivariate adaptive regression splinesbusiness.industryGeologyMars Exploration ProgramPollution020801 environmental engineeringCheck dam Machine learning techniques Sediment deposition rate (SR) Structure-from-motion (SfM) Unmanned aerial vehicle (UAV)Support vector machineArtificial intelligencebusinesscomputerCheck dam
researchProduct

Investigating Novice Developers’ Code Commenting Trends Using Machine Learning Techniques

2023

Code comments are considered an efficient way to document the functionality of a particular block of code. Code commenting is a common practice among developers to explain the purpose of the code in order to improve code comprehension and readability. Researchers investigated the effect of code comments on software development tasks and demonstrated the use of comments in several ways, including maintenance, reusability, bug detection, etc. Given the importance of code comments, it becomes vital for novice developers to brush up on their code commenting skills. In this study, we initially investigated what types of comments novice students document in their source code and further categoriz…

luokitus (toiminta)Numerical Analysismachine learning techniquesohjelmistokehittäjätvasta-alkajatTheoretical Computer Sciencesource code commentsComputational MathematicskoneoppiminenclassificationComputational Theory and Mathematicssource code comments; classification; machine learning techniqueslähdekooditohjelmointiohjelmistokehitysAlgorithms; Volume 16; Issue 1; Pages: 53
researchProduct