Suchergebnisse - "random forest algorithm"
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Machine learning for the selection of carbon-based materials for tetracycline and sulfamethoxazole adsorption
ISSN: 1385-8947, 1873-3212Veröffentlicht: Elsevier B.V 15.02.2021Veröffentlicht in Chemical engineering journal (Lausanne, Switzerland : 1996) (15.02.2021)“… [Display omitted] •Antiobiotics adsorption on carbon-based materials was modeled by machine learning.•Random forest showed best prediction accuracy than GBT …”
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Integrating machine learning with lateral flow immunoassay for ultrafast and sensitive tadalafil detection
ISSN: 0308-8146, 1873-7072, 1873-7072Veröffentlicht: England Elsevier Ltd 01.01.2026Veröffentlicht in Food chemistry (01.01.2026)“… Tadalafil, a phosphodiesterase type 5 inhibitor frequently detected in functional foods and dietary supplements, poses significant risks. To enable sensitive …”
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Flood disaster risk assessment based on random forest algorithm
ISSN: 0941-0643, 1433-3058Veröffentlicht: 01.03.2022Veröffentlicht in Neural computing & applications (01.03.2022)Volltext
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Predicting the performance and emissions of an HCCI-DI engine powered by waste cooking oil biodiesel with Al2O3 and FeCl3 nano additives and gasoline injection – A random forest machine learning approach
ISSN: 0016-2361, 1873-7153Veröffentlicht: Elsevier Ltd 01.02.2024Veröffentlicht in Fuel (Guildford) (01.02.2024)“… •Energy utilization from waste cooking oil is extensively studied.•Al2O3 and FeCl3 were used as an ignition enhancer to reduce emissions.•Smoke, HC and CO …”
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Integrated assessment of dissolved oxygen dynamics using optimized M-K trend detection and ridge regression in the Middle and Lower Yellow River Basin
ISSN: 0048-9697, 1879-1026, 1879-1026Veröffentlicht: Netherlands Elsevier B.V 20.11.2025Veröffentlicht in The Science of the total environment (20.11.2025)“… The accurate prediction and comprehensive analysis of dissolved oxygen (DO) are essential for maintaining water quality and ecosystem health in watershed …”
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Large group activity security risk assessment and risk early warning based on random forest algorithm
ISSN: 0167-8655, 1872-7344Veröffentlicht: Amsterdam Elsevier B.V 01.04.2021Veröffentlicht in Pattern recognition letters (01.04.2021)“… •With the continuous development of artificial intelligence, machine learning, as an indispensable means to realize artificial intelligence, is constantly …”
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Prediction of the uniaxial compressive strength of rocks from simple index tests using a random forest predictive model
ISSN: 1631-0721, 1873-7234Veröffentlicht: Académie des sciences 01.01.2020Veröffentlicht in Comptes rendus. Mecanique (01.01.2020)“… Uniaxial compressive strength (UCS) is an important mechanical parameter for stability assessments in rock mass engineering. In practice, obtaining the UCS …”
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Perovskites informatics: Studying the impact of thicknesses, doping, and defects on the perovskite solar cell efficiency using a machine learning algorithm
ISSN: 0894-3370, 1099-1204Veröffentlicht: Chichester, UK John Wiley & Sons, Inc 01.03.2024Veröffentlicht in International journal of numerical modelling (01.03.2024)“… The integration of machine learning (ML) models in studying, investigating, and optimizing various electronic devices and materials has significantly glow up …”
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Sentiment Analysis of 'Free Lunch for Children' Policy on Social Media X Using Random Forest Algorithm
ISSN: 2656-5935, 2656-4882Veröffentlicht: Informatics Department, Faculty of Computer Science Bina Darma University 22.03.2025Veröffentlicht in Journal of information systems and informatics (Palembang.Online) (22.03.2025)“… The concept of a welfare state emphasizes the main role of the government in providing protection and improving welfare such as health and education to its …”
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Machine learning to predict complications after salvage surgery in head and neck cancers
ISSN: 0901-5027, 1399-0020, 1399-0020Veröffentlicht: Denmark Elsevier Inc 17.11.2025Veröffentlicht in International journal of oral and maxillofacial surgery (17.11.2025)“… The aim of this study was to develop a machine learning classification model that can forecast salvage surgery complications. This was a retrospective analysis …”
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Comparing and Predicting Hepatic Encephalopathy Complications Using Random Forest Algorithm in Active Men
ISSN: 2423-5830, 2423-5830Veröffentlicht: Negah Institute for Scientific Communication 01.01.2025Veröffentlicht in Physical treatments (01.01.2025)“… Purpose: Liver diseases are among the most common disorders worldwide. For liver transplant patients, the presence of postoperative problems increases the …”
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Are precipitation concentration and intensity changing in Bangladesh overtimes? Analysis of the possible causes of changes in precipitation systems
ISSN: 0048-9697, 1879-1026, 1879-1026Veröffentlicht: Netherlands Elsevier B.V 10.11.2019Veröffentlicht in The Science of the total environment (10.11.2019)“… A comprehensive understanding of the changing behaviors of precipitation concentration and intensity plays a pivotal role in water resource management. Hence, …”
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A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility
ISSN: 0341-8162, 1872-6887Veröffentlicht: Elsevier B.V 01.04.2017Veröffentlicht in Catena (Giessen) (01.04.2017)“… The main purpose of the present study is to use three state-of-the-art data mining techniques, namely, logistic model tree (LMT), random forest (RF), and …”
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Low-cost, syringe based ion-selective electrodes for the evaluation of potassium in food products and pharmaceuticals
ISSN: 0013-4686Veröffentlicht: Elsevier Ltd 20.12.2024Veröffentlicht in Electrochimica acta (20.12.2024)“… •Development of low-cost ion-selective electrodes made from disposable syringes.•Standard quantification of potassium is not precise for samples of high ionic …”
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Modeling of Feature Selection Based on Random Forest Algorithm and Pearson Correlation Coefficient
ISSN: 1742-6588, 1742-6596Veröffentlicht: Bristol IOP Publishing 01.04.2022Veröffentlicht in Journal of physics. Conference series (01.04.2022)“… This paper establishes a feature selection model to selects 20 molecular descriptors of compounds with the most significant influence on biological activity …”
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Geophysical prediction technology for sweet spots of continental shale oil: A case study of the Lianggaoshan Formation, Sichuan Basin, China
ISSN: 0016-2361Veröffentlicht: Elsevier Ltd 01.06.2024Veröffentlicht in Fuel (Guildford) (01.06.2024)“… •High-precision data volume of parameters was derived from 3D seismic data using the nonlinear pre-stack AVO inversion methodology.•It correlated elastic …”
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Machine learning approach for predicting personal thermal comfort in air conditioning offices in Malaysia
ISSN: 0360-1323Veröffentlicht: Elsevier Ltd 01.12.2024Veröffentlicht in Building and environment (01.12.2024)“… The existing machine learning based models for personal thermal comfort have traditionally focused on physiological and psychological variations among …”
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Machine learning in health condition check-up: An approach using Breiman’s random forest algorithm
ISSN: 2665-9174, 2665-9174Veröffentlicht: Elsevier 01.10.2022Veröffentlicht in Measurement. Sensors (01.10.2022)“… Nowadays majority of the college students' physical condition is worrying. They are not physically and also mentally healthy. If so, why? Their selection of …”
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Persistent Overactive Cytotoxic Immune Response in a Spanish Cohort of Individuals With Long-COVID: Identification of Diagnostic Biomarkers
ISSN: 1664-3224, 1664-3224Veröffentlicht: Switzerland Frontiers Media S.A 25.03.2022Veröffentlicht in Frontiers in immunology (25.03.2022)“… Long-COVID is a new emerging syndrome worldwide that is characterized by the persistence of unresolved signs and symptoms of COVID-19 more than 4 weeks after …”
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RETRACTED: A Physics‐Aware Machine Learning‐Based Framework for Minimizing Prediction Uncertainty of Hydrological Models
ISSN: 0043-1397, 1944-7973Veröffentlicht: Washington John Wiley & Sons, Inc 01.06.2023Veröffentlicht in Water resources research (01.06.2023)“… Modeling hydrological processes for managing the available water resources effectively is often complex due to the existence of high nonlinearity, and the …”
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