Suchergebnisse - "light gradient boosting algorithm"

Decision Tree with Light Gradient Boosting Algorithm for University Teacher Performance Evaluation

Autoren: Jianxun Guo Beibei Zheng Lei Zhang et al.

Quelle: 2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS). :1-5

An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm

Autoren: Roohie Naaz Mir Vipul Sharma

Quelle: Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 3, Pp 615-626 (2022)

Schlagwörter: Ant colony optimization, Electronic computers. Computer science, Light gradient boosting algorithm, 0202 electrical engineering, electronic engineering, information engineering, Image watermarking, Fitness function, QA75.5-76.95, 02 engineering and technology, Time enhancement

Zugangs-URL: https://doaj.org/article/7cd0dcb2b5094bb996886acf854fcd8e
https://www.sciencedirect.com/science/article/pii/S1319157818310322

An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm.

Autoren: Sharma, Vipul Mir, Roohie Naaz

Quelle: Journal of King Saud University - Computer & Information Sciences. Mar2022, Vol. 34 Issue 3, p615-626. 12p.

Schlagwörter: Ant algorithms, Boosting algorithms, Digital watermarking, Feature extraction, Discrete cosine transforms, Machine learning

College student mental health assessment: Predictive models based on machine learning and feature importance analysis.

Autoren: Liu, Cheng Ji, Lin Lu, Juncheng et al.

Quelle: Molecular & Cellular Biomechanics; 2025, Vol. 22 Issue 3, p1-21, 21p

Schlagwörter: MENTAL health, MACHINE learning, PSYCHOTHERAPY, COLLEGE students, PREDICTION models, QUANTITATIVE research, AFFECTIVE disorders, SYMPTOM Checklist-90-Revised

Product Recommendation System With Machine Learning Algorithms for SME Banking.

Autoren: Met, Ilker Erkoc, Ayfer Seker, Sadi Evren et al.

Quelle: International Journal of Intelligent Systems; 10/28/2024, Vol. 2024, p1-21, 21p

Schlagwörter: MACHINE learning, RECOMMENDER systems, BEHAVIORAL assessment, BANKING industry, CONSUMERS

基于高光谱成像技术的高粱农药残留 种类检测研究. (Chinese)

Alternate Title: Detection of pesticide residue types in sorghum based on hyperspectral imaging technology research. (English)

Autoren: 张嘉洪 何 林 胡新军 et al.

Quelle: Journal of Food Safety & Quality; Oct2023, Vol. 14 Issue 20, p209-217, 9p

Vaccine hesitancy in the post-vaccination COVID-19 era: a machine learning and statistical analysis driven study.

Autoren: Gupta, Himanshu Verma, Om Prakash

Quelle: Evolutionary Intelligence; Jun2023, Vol. 16 Issue 3, p739-757, 19p

Rapid nondestructive detection of peanut varieties and peanut mildew based on hyperspectral imaging and stacked machine learning models.

Autoren: Qingsong Wu Lijia Xu Zhiyong Zou et al.

Quelle: Frontiers in Plant Science; 11/10/2022, Vol. 13, p1-14, 14p

Schlagwörter: PEANUTS, MACHINE learning, BOOSTING algorithms, MILDEW, CROP yields, SEED yield, NONDESTRUCTIVE testing

Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer.

Autoren: Osman, Mohamed Hosny Mohamed, Reham Hosny Sarhan, Hossam Mohamed et al.

Quelle: Cancer Research & Treatment; Apr2022, Vol. 54 Issue 2, p517-524, 8p

Schlagwörter: OVERALL survival, MACHINE learning, COLORECTAL cancer, RECEIVER operating characteristic curves, BOOSTING algorithms

NmRF: identification of multispecies RNA 2'-O-methylation modification sites from RNA sequences.

Autoren: Ao, Chunyan Zou, Quan Yu, Liang

Quelle: Briefings in Bioinformatics; Jan2022, Vol. 23 Issue 1, p1-13, 13p

Schlagwörter: RNA modification & restriction, TRANSFER RNA, FEATURE selection, RANDOM forest algorithms, METHYL groups, MACHINE learning, BOOSTING algorithms

Employing advanced supervised machine learning approaches for predicting micronutrient intake status among children aged 6–23 months in Ethiopia

Autoren: Alemu Birara Zemariam Molalign Aligaz Adisu Aklilu Abera Habesse et al.

Quelle: Frontiers in Nutrition, Vol 11 (2024)

Schlagwörter: micronutrient supplementation, children, machine learning algorithm, prediction, Ethiopia, Nutrition. Foods and food supply, TX341-641

Dateibeschreibung: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fnut.2024.1397399/full; https://doaj.org/toc/2296-861X

Zugangs-URL: https://doaj.org/article/96a5011b78514daea306ec3c2917d46f

Enhancing anti-money laundering via Fourier-based contrastive learning.

Autoren: Tong, Meihan Wang, Shuai

Quelle: International Journal of Data Science & Analytics; Nov2025, Vol. 20 Issue 6, p6527-6538, 12p

RDHNet: Reversible Data Hiding Method for Securing Colour Images Using AlexNet and Watershed Transform in a Fusion Domain.

Autoren: Eltoukhy, Mohamed Meselhy Alsubaei, Faisal S. Abdel‐Aziz, Mostafa M. et al.

Quelle: CAAI Transactions on Intelligence Technology; Oct2025, Vol. 10 Issue 5, p1422-1445, 24p

Schlagwörter: DATA privacy, REVERSIBLE data hiding (Computer science), IMAGE encryption, WATERSHEDS, DATA security, FEATURE extraction, MEDICAL photography, CRYPTOGRAPHY

Intelligent Fault Management for Photovoltaic System using Cross-Correlation and Machine Learning.

Autoren: Nwamuo, C. U. Ojike, O. Enibe, S. O.

Quelle: Nigerian Journal of Technological Development; Sep2025, Vol. 22 Issue 4, p142-155, 14p

Schlagwörter: OPTIMIZATION algorithms, PHOTOVOLTAIC power systems, STANDARD deviations, CROSS correlation, MACHINE learning

How effective oversampling techniques are in classifying potentially hazardous asteroids.

Autoren: Sadman, Md. Hossain, Mir Sakhawat

Quelle: European Physical Journal Plus; Sep2025, Vol. 140 Issue 9, p1-14, 14p

Physics-Informed Surrogate Modelling in Fire Safety Engineering: A Systematic Review.

Autoren: Yarmohammadian, Ramin Put, Florian Van Coile, Ruben

Quelle: Applied Sciences (2076-3417); Aug2025, Vol. 15 Issue 15, p8740, 36p

Schlagwörter: FIRE protection engineering, MACHINE learning, REDUCED-order models, PREDICTION models, OPTIMIZATION algorithms, COMPUTER simulation

Prediction of Type- 2 Diabetes using the LGBM Classifier Methods and Techniques

Autoren: et. al., B. Shamreen Ahamed

Quelle: Turkish Journal of Computer and Mathematics Education (TURCOMAT); Vol. 12 No. 12 (2021); 223-231; 3048-4855

Index Begriffe: info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion

URL: https://turcomat.org/index.php/turkbilmat/article/view/7304
https://turcomat.org/index.php/turkbilmat/article/view/7304/5922
https://turcomat.org/index.php/turkbilmat/article/view/7304/5922

MultiV_Nm: a prediction method for 2′-O-methylation sites based on multi-view features.

Autoren: Bai, Lei Liu, Fei Wang, Yile et al.

Quelle: Frontiers in Genetics; 2025, p1-14, 14p

Schlagwörter: CONVOLUTIONAL neural networks, RNA modification & restriction, FEATURE extraction, DRUG target, THERAPEUTICS

A Comparative Study of Ensemble Machine Learning and Explainable AI for Predicting Harmful Algal Blooms.

Autoren: Mermer, Omer Zhang, Eddie Demir, Ibrahim

Quelle: Big Data & Cognitive Computing; May2025, Vol. 9 Issue 5, p138, 27p

Schlagwörter: MACHINE learning, WATER quality management, ALGAL blooms, ARTIFICIAL intelligence, WATER quality

Forecasting Hospitalization for Adult Asthma Patients in Emergency Departments Based on Multiple Environmental and Clinical Factors.

Autoren: Xi, Hanxu Zhang, Yudi Zuo, Rui et al.

Quelle: Journal of Asthma & Allergy; May2025, Vol. 18, p861-876, 16p

Schlagwörter: EMERGENCY room visits, RECEIVER operating characteristic curves, ASTHMATICS, OXYGEN saturation, SUPPORT vector machines