Suchergebnisse - "KNN algorithm"

Predicting foreign exchange in emerging markets with a nearest neighbor approach: fundamentals versus online attention indicators

Autoren: Klender Cortez

Quelle: Financial Innovation, Vol 11, Iss 1, Pp 1-20 (2025)

Schlagwörter: Exchange rate prediction, Google trends, Machine learning, KNN algorithm, Public finance, K4430-4675, Finance, HG1-9999

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2199-4730

Zugangs-URL: https://doaj.org/article/616f58d3bb8849a8a81297f9b0557253

El Consumo Turístico nacional y extranjero en las comunidades autónomas de España (2002-2019)

Autoren: Diana-Valeria Delgado-Campuzano Jazmin-Jessenia Peñafiel-León Byron-Wladimir Oviedo-Bayas et al.

Quelle: idUS. Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)

Schlagwörter: Tourism demand, Consumption, Tourist destinations, Consumo turístico, Demanda turística, Destinos turísticos, Data analysis, Algoritmo KNN, Análisis de datos, KNN algorithm

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11441/174248

‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌

Autoren: Haoran Ge Jiyong Zhang Congbo Ma et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-16 (2025)

Schlagwörter: Rockburst prediction, Eliminating outliers, Undersampling, KNN algorithm, Machine learning, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/60ea24c784d14ede8b702c3759331aae

Network intrusion detection based on improved KNN algorithm

Autoren: Hongsheng Bao Jie Gao

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-19 (2025)

Schlagwörter: KNN algorithm, Network intrusion, Three branch decision-making, Incremental learning, Classification, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/9079828383774ee094684e9519501ea2

Medical based Decision Support System for Stroke Prediction and its Types using ML Algorithms

Autoren: Navya K S Aishwarya N

Schlagwörter: Stroke prediction, Machine learning, KNN algorithm, Bayesian classifier, Naive Bayes, Random Forest, Decision support system, Data preprocessing, Ischemic stroke

Prediction of Home Loan Approval with Machine Learning

Autoren: Gamze Güder Utku Köse

Quelle: Volume: 4, Issue: 287-95
Advances in Artificial Intelligence Research

Schlagwörter: Makine Öğrenme (Diğer), 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 0501 psychology and cognitive sciences, 02 engineering and technology, KNN algorithm, Random forest algorithm, Support vector machines, Logistic regression, Machine Learning (Other)

Dateibeschreibung: application/pdf

Zugangs-URL: https://dergipark.org.tr/tr/pub/aair/issue/89140/1585994

Application of an intelligent English text classification model with improved KNN algorithm in the context of big data in libraries

Autoren: Qinwen Xu

Quelle: Systems and Soft Computing, Vol 7, Iss , Pp 200186- (2025)

Schlagwörter: K-means clustering, KNN algorithm, Category average distance, Intelligent classification of English texts, Big data analysis, Information technology, T58.5-58.64, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2772941925000043; https://doaj.org/toc/2772-9419

Zugangs-URL: https://doaj.org/article/d639db03796f4944bf81b44c8f825601

Machine learning model for classifying high school students’ academic performance in mathematics amidst the COVID-19 context

Autoren: Gisella Luisa Elena Maquen-Niño Moisés Alvin Miguel_Flores Leysi Yarely Aurich_Mio et al.

Quelle: Journal of Technology and Science Education, Vol 15, Iss 2, Pp 322-334 (2025)

Schlagwörter: machine learning, classification model, academic performance, mathematics, knn algorithm, Education, Special aspects of education, LC8-6691, Technology, Engineering (General). Civil engineering (General), TA1-2040

Dateibeschreibung: electronic resource

Relation: https://www.jotse.org/index.php/jotse/article/view/2945; https://doaj.org/toc/2013-6374

Zugangs-URL: https://doaj.org/article/eba2c802970f4fee89e21233ab533e4c

A Data-Driven Incident Detection Method for the Safe Operation of Molten Salt Fast Reactors

Autoren: Abrate, Nicolò Caruso, Nicolò Dulla, Sandra et al.

Quelle: Proceedings of International conference PHYSOR 2024, San Francisco, CA, April 2024

Schlagwörter: Molten Salt Reactors, Plant monitoring, Incident detection, Singular Value Decomposition, kNN algorithm

Verifiable secure image retrieval for cloud-assisted IoT environments

Autoren: GUO Jiaqi MA Zhi WANG Wensheng et al.

Quelle: Tongxin xuebao, Vol 46, Pp 28-44 (2025)

Schlagwörter: secure image retrieval, secure kNN algorithm, LWE problem, IoT, Telecommunication, TK5101-6720

Dateibeschreibung: electronic resource

Relation: http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2025050; https://doaj.org/toc/1000-436X

Zugangs-URL: https://doaj.org/article/97df7156319c49d691157a2111db46d3

Hybrid Particle Swarm Optimization and Feedforward Neural Network Model for Enhanced Prediction of Gas Turbine Emissions

Autoren: Awad, A. N. Jarad, T. Sh.

Quelle: International Journal of Energy Production and Management. 9:97-105

Schlagwörter: PREDICTION ACCURACY MEASUREMENTS, 13. Climate action, GAS TURBINE EMISSIONS PREDICTION, K-NEAREST NEIGHBOR (KNN) ALGORITHM, 7. Clean energy, FNN-BASED PSO APPROACH

Zugangs-URL: http://elar.urfu.ru/handle/10995/137281

Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks

Autoren: Nadia Shamshad Lei Wang Kiran Saleem et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-17 (2025)

Schlagwörter: Machine Learning, KNN-Algorithm, accuracy rate, Localization, Prediction, NS-3, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/3467b267c4b44ed6b7b4077cba5c6326

Determination of the Classification Success of KNN Algorithm Distance Metric Methods on Wheat Seeds Dataset

Autoren: Ahmet ÇELİK

Quelle: Volume: 23, Issue: 5 1142-1149
Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi

Schlagwörter: 2. Zero hunger, Distance Metric Methods, Machine learning, Classification, Seeds dataset, Distance metric methods, Random sampling, KNN algorithm, Uzaklık Metrik Yöntemleri, 15. Life on land, Seeds Dataset, Machine Learning, KNN Algorithm, Random Sampling, Makine öğrenmesi, Sınıflandırma, Seeds veri seti, KNN algoritması, Uzaklık metrik yöntemleri, Rastgele örnekleme, Yapay Zeka, KNN Algoritması, Artificial Intelligence, Makine Öğrenmesi, Seeds Veri Seti, Rastgele Örnekleme

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11630/12107
https://dergipark.org.tr/tr/pub/akufemubid/issue/80634/1263900

An Intelligent Prediction Model for IPL Winners Using Deep Learning and KNN Algorithm

Autoren: Harshitha B Thanushri R Nazima Khanum et al.

Schlagwörter: IPL, Prediction Model, Machine Learning, KNN Algorithm, Neural learning, Sports Analytics, Regression Model, Data Science

A bitcoin service community classification method based on Random Forest and improved KNN algorithm

Autoren: Muyun Gao Shenwen Lin Xin Tian et al.

Quelle: IET Blockchain, Vol 4, Iss 3, Pp 276-286 (2024)

Schlagwörter: Electronic computers. Computer science, Random Forest algorithm, community entity classification, 0202 electrical engineering, electronic engineering, information engineering, improved KNN algorithm, QA75.5-76.95, 02 engineering and technology, feature filtering, Bitcoin

Zugangs-URL: https://doaj.org/article/e1c0b2d2372b4090a9f84a47a2e9dd36

IT diagnostics of Parkinson's disease based on voice markers and decreased motor activity

Autoren: Vishniakou, U. А. Yiwei, X.

Quelle: Системный анализ и прикладная информатика, Vol 0, Iss 4, Pp 51-57 (2024)

Schlagwörter: machine learning, 0202 electrical engineering, electronic engineering, information engineering, parkinsons disease recognition, Information technology, 02 engineering and technology, knn algorithm, bayesian neural network, T58.5-58.64

Zugangs-URL: https://doaj.org/article/7483e2c2fb9646bfaeac36a68479654a
https://rep.bntu.by/handle/data/139566

An Enhanced Frequency Analysis and Machine Learning Based Approach for Open Circuit Failures in PV Systems

Autoren: Mauricio Lavador-Osorio Marco-Antonio Zuñiga-Reyes José M. Álvarez-Alvarado et al.

Quelle: IEEE Access, Vol 12, Pp 96342-96357 (2024)

Schlagwörter: dynamic impedance in photovoltaic systems, discrete Fourier transform, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, 7. Clean energy, Fault detection in photovoltaic systems, open circuit fault detection, KNN algorithm, TK1-9971

Zugangs-URL: https://doaj.org/article/e1518953132440d99b45f1d4785de8f2

Simulation of Ground Visibility Based on Atmospheric Boundary Layer Data Using K-Nearest Neighbors and Ensemble Model Algorithms

Autoren: Ruolan Liu Shujie Yuan Duanyang Liu et al.

Quelle: Aerosol and Air Quality Research, Vol 24, Iss 12, Pp 1-19 (2024)

Schlagwörter: KNN algorithm, Ensemble model algorithm, Visibility simulation, Fog-Haze, Machine learning, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1680-8584; https://doaj.org/toc/2071-1409

Zugangs-URL: https://doaj.org/article/1cc9d026201f41a3a89c5fe37dc4adf3

Colorectal cancer prognosis based on dietary pattern using synthetic minority oversampling technique with K-nearest neighbors approach

Autoren: S. Thanga Prasath C. Navaneethan

Quelle: Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)

Schlagwörter: Colorectal cancer prognosis, Dietary, Dairy products, Machine learning (ML), Synthetic minority oversampling technique-SMOTE, KNN algorithm (KNN), Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/427a983c3231403cbdc85d10c82644b0

Analysis and implementation of computation offloading in fog architecture

Autoren: Gupta, Prince Sharma, Rajeev Gupta, Sachi et al.

Quelle: IAES International Journal of Robotics and Automation (IJRA); Vol 14, No 3: December 2025; 479-492 ; 2722-2586 ; 2089-4856 ; 10.11591/ijra.v14i3

Schlagwörter: Adaptive boosting, Computation offloading, Edge computing, Fog computing, KNN algorithm, Latency optimization, Resource allocation

Dateibeschreibung: application/pdf

Relation: https://ijra.iaescore.com/index.php/IJRA/article/view/21034/13237; https://ijra.iaescore.com/index.php/IJRA/article/view/21034

Verfügbarkeit: https://ijra.iaescore.com/index.php/IJRA/article/view/21034
https://doi.org/10.11591/ijra.v14i3.pp479-492