Results 271 to 280 of about 150,441 (331)
Some of the next articles are maybe not open access.
Insights into geospatial heterogeneity of landslide susceptibility based on the SHAP-XGBoost model.
Journal of Environmental Management, 2023The spatial heterogeneity of landslide influencing factors is the main reason for the poor generalizability of the susceptibility evaluation model.
Junyi Zhang +6 more
semanticscholar +1 more source
Crude oil price forecasting using XGBoost
2017 International Conference on Computer Science and Engineering (UBMK), 2017One of the most important role of economic variables in today's world countries are the price and the change of the price of crude oil. Changes in the price of crude oil have a very critical role in terms of treasury and budget, both in company and state planning.
Gumus, Mesut, Kiran, Mustafa S.
openaire +2 more sources
Beyond XGBoost and SHAP: Unveiling true feature importance.
Journal of Hazardous MaterialsThis paper outlines key machine learning principles, focusing on the use of XGBoost and SHAP values to assist researchers in avoiding analytical pitfalls.
Y. Takefuji
semanticscholar +1 more source
Single-Sentence Compression using XGBoost
International Journal of Information Retrieval Research, 2019Sentence compression is known as presenting a sentence in a fewer number of words compared to its original one without changing the meaning. Recent works on sentence compression formulates the problem as an integer linear programming problem (ILP) then solves it using an external ILP-solver which suffers from slow running time.
Deepak Sahoo +1 more
openaire +1 more source
PM2.5 Prediction Based on XGBoost
2020 7th International Conference on Information Science and Control Engineering (ICISCE), 2020Haze pollution is a serious weather condition which occurs frequently in mainland China. As there has been an increasing worldwide research interest around topics in environment protection and human health, PM2.5 concentration is regarded as a vital index to reflect the air quality.
Liumei Zhang +3 more
openaire +1 more source
Prediction model for spontaneous combustion temperature of coal based on PSO-XGBoost algorithm
Scientific ReportsThe construction of a predictive model that accurately reflects the spontaneous combustion temperature of coal in goaf is fundamental to monitoring and early warning systems for thermodynamic disasters, including coal spontaneous combustion and gas ...
Hui Zhuo +5 more
semanticscholar +1 more source
RAINFALL PREDICTION USING XGBOOST
International Scientific Journal of Engineering and ManagementIndia is a farming nation and its economy heavily depends on crop productivity and rainfall. Rainfall prediction is necessary and required to all farmers in order to analyze the crop productivity. Rainfall Prediction is the use of science and technology for forecasting the condition of the atmosphere. It is necessary to precisely calculate the rainfall
Erusu Kata Raju Reddy, Thamada Saikumar
openaire +1 more source
XGBoost-based method for flash flood risk assessment
Journal of Hydrology, 2021Flash flood risk assessment, a widely applied technology in preventing catastrophic flash flood disasters, has become the current research hotspot. However, most existing machine learning methods for assessing flash flood risk rely on a single classifier,
M. Ma +6 more
semanticscholar +1 more source
Estimating hair density with
AbstractObjectivesHair density estimation is crucial in dermatology and trichology; however, manual counting is time‐consuming and error‐prone. Although automated approaches have been developed using image processing, neural networks, and deep learning, creating a robust and widely applicable method remains challenging.
Yi‐Fan Wang +3 more
openaire +2 more sources