Suchergebnisse - "Random forest algorithms"

Optimization and prediction of a novel preignition in hydrogen direct injection engines through experimentation and the Random forest algorithms von Liang, Zhendong, Xie, Fangxi, Guo, Zezhou, Wang, Zhongshu, Dou, Huili, Wang, Bin, Shen, Bo

“… •The novel preignition event (PEMC) was explored on HDI engines.•PEMC event occurred in the early/mid compression stroke and with the peak pressure at …”
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Advanced predictive modelling of urban expansion and land surface temperature dynamics using multi-scale machine learning approaches von Bindajam, Ahmed Ali, Mallick, Javed, Hang, Hoang Thi, Singh, Chander Kumar

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Machine learning intelligently selects feature values to construct a sensor array based on tri-functional Mn-doped covalent organic polymer nanozymes for identifying flavonoid compounds von Zhang, Guo-Qi, Jiang, Wen-Cai, Li, Xiao-Mei, Li, Ren-Jie, Feng, Yi, Nai, Ri-Ge Li, Cheng, Hui-Lin, Hou, Zhi-Bo, Luo, Xiao-Jun, Zhao, Yan

“… Herein, a novel tri-functional Mn-doped covalent organic polymer nanozyme (Mn-COP) with peroxidase-like, oxidase-like, and laccase-like activities was …”
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Integrated bulk and single-cell RNA sequencing identifies oxidative stress signatures of radiation-induced lung injury in mice through machine learning von Huang, Wei, Deng, Guanhua, Zhang, Qinghua, Lv, Fengquan, Xie, Dehuan, Ren, Chen, Du, Shasha, Tan, Peixin

“… Radiation induced lung injury (RILI) is a common complication in patients undergoing thoracic radiotherapy. At present, there are no effective early diagnostic …”
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Assessing models for prediction of some soil chemical properties from portable X-ray fluorescence (pXRF) spectrometry data in Brazilian Coastal Plains von Andrade, Renata, Silva, Sérgio Henrique Godinho, Weindorf, David C., Chakraborty, Somsubhra, Faria, Wilson Missina, Mesquita, Luiz Felipe, Guilherme, Luiz Roberto Guimarães, Curi, Nilton

“… Portable X-ray fluorescence (pXRF) spectrometry is becoming increasingly popular for predicting soil properties worldwide. However, there are still very few …”
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Estimating the soil salinity over partially vegetated surfaces from multispectral remote sensing image using non-negative matrix factorization von Liu, Ya, Zhang, Fangfang, Wang, Changkun, Wu, Shiwen, Liu, Jie, Xu, Aiai, Pan, Kai, Pan, Xianzhang

“… Multispectral remote sensing technique has been extensively applied in recent years for the detection of soil salinity on bare soil; however, multispectral …”
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Involvement of Slab‐Derived Fluid in the Generation of Cenozoic Basalts in Northeast China Inferred From Machine Learning von Zhao, Yong, Zhang, Yigang, Geng, Ming, Jiang, Jilian, Zou, Xinyu

“… The origin and involvement of fluid in the generation of Cenozoic basalts in Northeast China are still under debate. Here we apply the machine learning methods …”
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Integration of spectral, spatial and morphometric data into lithological mapping: A comparison of different Machine Learning Algorithms in the Kurdistan Region, NE Iraq von Othman, Arsalan A., Gloaguen, Richard

“… [Display omitted] •Adding geomorphic indices in the dataset increases the classification accuracy.•The best overall accuracy is achieved by the Random Forest …”
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Parent material distribution mapping from tropical soils data via machine learning and portable X-ray fluorescence (pXRF) spectrometry in Brazil von Mancini, Marcelo, Weindorf, David C., Silva, Sérgio Henrique Godinho, Chakraborty, Somsubhra, Teixeira, Anita Fernanda dos Santos, Guilherme, Luiz Roberto Guimarães, Curi, Nilton

“… Knowledge about parent material (PM) is crucial to understand the properties of overlying soils. Assessing PM of very deep soils, however, is not easy …”
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Identification and Validation of TFF3 as a Diagnostic Biomarker and Therapeutic Agent for Bronchopulmonary Dysplasia von Zou, Zhenzhuang, Fu, Li, Liu, Jiaying, He, Yunfei, Huang, Bo, Wang, Shaohua

“… ABSTRACT Background Bronchopulmonary dysplasia (BPD) is a common and severe complication in preterm infants, driven by oxidative stress, inflammation, and …”
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Comparative analysis of machine learning models for the detection of fraudulent banking transactions von Preciado Martínez, Pedro María, Reier Forradellas, Ricardo Francisco, Garay Gallastegui, Luis Miguel, Náñez Alonso, Sergio Luis

“… This research presents a comparative analysis of machine learning models for detecting fraudulent banking transactions, a growing problem in the digital …”
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Tree-ring-width based streamflow reconstruction based on the random forest algorithm for the source region of the Yangtze River, China von Li, Jun, Wang, Zhaoli, Lai, Chengguang, Zhang, Zhenxing

“… Extending series of river streamflow based on tree-ring reconstruction is of scientific and practical importance for understanding hydrological or …”
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Continuous non-contact monitoring of neonatal activity von Addison, Paul S., Gerstmann, Dale, Clemmer, Jeffrey, Nelson, Rena, Gunturi, Mridula, Montgomery, Dean, Ajizian, Sam

“… Purpose Neonatal activity is an important physiological parameter in the neonatal intensive care unit (NICU). The degree of neonatal activity is associated …”
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Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China von Tian, Huiling, Zhu, Jianhua, He, Xiao, Chen, Xinyun, Jian, Zunji, Li, Chenyu, Ou, Qiangxin, Li, Qi, Huang, Guosheng, Liu, Changfu, Xiao, Wenfa

“… Estimating the volume growth of forest ecosystems accurately is important for understanding carbon sequestration and achieving carbon neutrality goals …”
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Impact analysis and optimization of notched high-gain Antipodal Vivaldi antenna using machine learning von Kumar Jaiswal, Pawan, Bhattacharya, Rajarshi

“… Optimizing antenna parameters without knowing their impact on the gain is a time-consuming and iterative process. This article shows how the Classification and …”
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A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008–2012, 2017–2021) von Kim, Min Seok, Choi, Young Wook, Prakash, Borghare Shubham, Lee, Youngju, Lim, Soo, Woo, Se Joon

“… Machine learning technology that uses available clinical data to predict diabetic retinopathy (DR) can be highly valuable in medical settings where fundus …”
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From geological to soil parent material maps - A random forest-supported analysis of geological map units and topography to support soil survey in South Tyrol von Gruber, Fabian E., Baruck, Jasmin, Mair, Volkmar, Geitner, Clemens

“… Parent material is an important factor of soil formation and consequently plays a dominant role in both traditional field soil survey and digital soil mapping …”
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Financial big data control and intelligent analysis method for investment decision of renewable energy projects von Li, Dongyun

“… With the increasing scarcity of conventional energy and environmental degradation, countries around the world are increasing their investment in renewable …”
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Teleconnections in spatial modelling von Behrens, Thorsten, MacMillan, Robert A., Viscarra Rossel, Raphael A., Schmidt, Karsten, Lee, Juhwan

“… In pedology, spatial context is relevant to soil-landscape systems on at least three different scales: i) the scale of quasi-local processes, which are …”
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Automated classification of metamorphosed coal from geophysical log data using supervised machine learning techniques von Maxwell, Kane, Rajabi, Mojtaba, Esterle, Joan

“… Identification of the extent of heat altered coals is important for coal mining and resource estimation because alteration directly affects key economic …”
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