Results 31 to 40 of about 38,464 (255)

Short-term Price Prediction in Initial Public Offerings Using XGBoost: Bist Technology Sector Example

Ekonomi, Politika & Finans Araştırmaları Dergisi
The aim of the study is to predict the closing price of the next trading day's stocks, of the initial public offering firms in the short term (between 5 and 10 days).
Ayse Merve Acılar, Gamze Şekeroğlu
doaj   +1 more source

Fuel flow prediction of domestic civil aircraft based on LSTM-XGBoost

Hangkong gongcheng jinzhan
The neural network model is widely used in fuel consumption prediction，but single model is less used in the application of civil aircraft because of its low prediction accuracy.
YANG Junli, LI Likun, QIAN Yu, TANG Shengxiang, YANG Peida   +4 more
doaj   +1 more source

XGBoost and Random Forest Algorithms: An in Depth Analysis

Pakistan Journal of Scientific Research, 2023
Machine learning is playing an increasingly important role in many facets of our lives as technology develops, including forecasting weather, figuring out social media trends, and predicting prices on the world market. This significance invoked the demand of some efficient predicting models that can easily handle complex data and provide maximum ...
null Sana Fatima, null Ayan Hussain, null Sohaib Bin Amir, null Muhammad Gulraiz Zahid Awan, null Syed Haseeb Ahmed, null Syed Muhammad Huzaifa Aslam   +5 more
openaire   +2 more sources

RESEARCH ON GEAR BOX FAULT DIAGNOSIS BASED ON DCNN AND XGBOOST ALGORITHM

Jixie qiangdu, 2020
In order to solve the problem of complex fault diagnosis of gearbox,the DCNN（ Deep Convolution Neural Network） was combined with the XGBoost（ e Xtreme Gradient Boosting） algorithm to establish the fault diagnosis model. Firstly,the DCNN Model was used to
ZHANG RongTao, CHEN ZhiGao, LI BinBin, JIAO Bin   +3 more
doaj  

Classification of Breast Cancer on the Strength of Potential Risk Factors with Boosting Models: A Public Health Informatics Application

Haseki Tıp Bülteni, 2022
Aim:The diagnosis of breast cancer can be accomplished using an algorithm or an early detection model of breast cancer risk via determining factors. In the present study, gradient boosting machines (GBM), extreme gradient boosting (XGBoost) and light ...
Sami Akbulut, Ipek Balikci Cicek, Cemil Colak   +2 more
doaj   +1 more source

Harnessing LSTM and XGBoost algorithms for storm prediction

Scientific Reports
AbstractStorms can cause significant damage, severe social disturbance and loss of human life, but predicting them is challenging due to their infrequent occurrence. To overcome this problem, a novel deep learning and machine learning approach based on long short-term memory (LSTM) and Extreme Gradient Boosting (XGBoost) was applied to predict storm ...
Ayyoub Frifra, Mohamed Maanan, Mehdi Maanan, Hassan Rhinane   +3 more
openaire   +5 more sources

Stock Price Prediction of Technology Enterprises Based on XGBoost Algorithm [PDF]

ITM Web of Conferences
Stock price prediction is a popular research field in the financial and big data industries. Over decades, researchers have leveraged various machine learning and deep learning algorithms to build many innovative models to predict stock prices, and ...
Zhai Songbo
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Applying interpretable machine learning algorithms to predict risk factors for permanent stoma in patients after TME

Frontiers in Surgery, 2023
ObjectiveThe purpose of this study was to develop a machine learning model to identify preoperative and intraoperative high-risk factors and to predict the occurrence of permanent stoma in patients after total mesorectal excision (TME).MethodsA total of ...
Yuan Liu, Songyun Zhao, Wenyi Du, Zhiqiang Tian, Hao Chi, Cheng Chao, Wei Shen   +6 more
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Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning

Cejing jishu
The lithology of the first member of the Maokou formation in the Middle Permian of Central Sichuan is complex and the longitudinal variation is large. There are many influencing factors and difficulty in the prediction of total organic carbon content, so
TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng   +5 more
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An eXtreme Gradient Boosting Algorithm Combining Artificial Bee Colony Parameters Optimized Technique for Single Sand Body Identification

IEEE Access, 2021
Due to the problems of traditional artificial single sand body identification methods such as strong subjectivity, heavy workload and low efficiency, we propose a fast and objective ABC-XGBoost.
Renze Luo, Liang Guo, Xingyu Li, Juanjuan Tuo, Canru Lei, Yang Zhou   +5 more
doaj   +1 more source