Suchergebnisse - "Population-based Vortex Search Algorithm"

PVS: a new population-based vortex search algorithm with boosted exploration capability using polynomial mutation

Autoren: Tahir Sağ

Quelle: Neural Computing and Applications. 34:18211-18287

Schlagwörter: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://aperta.ulakbim.gov.tr/record/255699

Anticipating Properties of Ultra-High-Performance Concrete through the K-Nearest Neighbor Algorithm

Autoren: Yonghoon Won

Quelle: Journal of Artificial Intelligence and System Modelling, Vol 03, Iss 03, Pp 15-33 (2025)

Schlagwörter: ultra-high-performance concrete, machine learning, k-nearest neighbor-based, giant trevally optimizer, population-based vortex search algorithm, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://jaism.bilijipub.com/article_230939_9da4fee65acae5a0b493196ad3f73fc8.pdf; https://doaj.org/toc/3041-850X

Zugangs-URL: https://doaj.org/article/ac83ac0a8b514aab81a1fd9d7fc7887b

Innovative Machine Learning Approach for Forecasting Student Performance in Degree Programs: A Case Study Using Naive Bayes Classification

Autoren: Nana Wang

Quelle: Journal of Applied Science and Engineering, Vol 29, Iss 3, Pp 639-653 (2025)

Schlagwörter: student performance, model, naive bayes classification, population-based vortex search algorithm, electric charged particles optimization, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Physics, QC1-999

Dateibeschreibung: electronic resource

Relation: http://jase.tku.edu.tw/articles/jase-202603-29-03-0015; https://doaj.org/toc/2708-9967; https://doaj.org/toc/2708-9975

Zugangs-URL: https://doaj.org/article/33eb370fd9674b359111f05aff4c0183

Applying Support Vector Regression-Based Hybrid Models for Modeling the Gasification Process

Autoren: Baofu Gong

Quelle: Journal of Applied Science and Engineering, Vol 28, Iss 6, Pp 1195-1208 (2024)

Schlagwörter: gasification modeling, machine learning, support vector regression, crystal structure algorithm, population-based vortex search algorithm, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Physics, QC1-999

Dateibeschreibung: electronic resource

Relation: http://jase.tku.edu.tw/articles/jase-202506-28-06-0003; https://doaj.org/toc/2708-9967; https://doaj.org/toc/2708-9975

Zugangs-URL: https://doaj.org/article/fb59c850573044e9aef1728545e785ed

Forecasting Residential Building Heating Load with an Innovative Gaussian Process Regression Method

Autoren: Xiaoyu Sun

Quelle: Journal of Applied Science and Engineering, Vol 28, Iss 6, Pp 1219-1231 (2024)

Schlagwörter: heating load, gaussian process regression, population-based vortex search algorithm, flow direction algorithms, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Physics, QC1-999

Dateibeschreibung: electronic resource

Relation: http://jase.tku.edu.tw/articles/jase-202506-28-06-0005; https://doaj.org/toc/2708-9967; https://doaj.org/toc/2708-9975

Zugangs-URL: https://doaj.org/article/aaf4a008ec494584ab5578946d1968a5

PVS: a new population-based vortex search algorithm with boosted exploration capability using polynomial mutation.

Autoren: Sağ, Tahir

Quelle: Neural Computing & Applications; Oct2022, Vol. 34 Issue 20, p18211-18287, 77p

Schlagwörter: SEARCH algorithms, METAHEURISTIC algorithms, POLYNOMIAL operators, POLYNOMIALS, ALGORITHMS

Anticipating Properties of Ultra-High-Performance Concrete through the KNearest Neighbor Algorithm.

Autoren: Won, Yonghoon

Quelle: Journal of Artificial Intelligence & System Modelling (JAISM); Sep2025, Vol. 3 Issue 3, p15-33, 19p

Schlagwörter: K-nearest neighbor classification, MACHINE learning, PREDICTION models, METAHEURISTIC algorithms, ARTIFICIAL intelligence, HIGH strength concrete

A hybrid Fox optimization algorithm with chaotic maps and polynomial mutation for clustering applications.

Autoren: Dağlı, İlker İnan, Onur Başçi̇ftçi̇, Fatih

Quelle: Evolving Systems; Dec2025, Vol. 16 Issue 4, p1-27, 27p

Machine learning-based prediction of compressive strength and slump in high-performance concrete.

Autoren: Zhang, Ruikun Meng, Chenyu

Quelle: Multiscale & Multidisciplinary Modeling, Experiments & Design; Nov2025, Vol. 8 Issue 10, p1-23, 23p

Hybrid Machine Learning Models for Optimized Potato Price Prediction

Autoren: Liping Liu

Quelle: Journal of Applied Science and Engineering, Vol 29, Iss 5, Pp 1123-1138 (2025)

Schlagwörter: potato prices, decision-making process, machine learning, light gradient boosting regression, stochastic paint optimizer, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Physics, QC1-999

Dateibeschreibung: electronic resource

Relation: http://jase.tku.edu.tw/articles/jase-202605-29-05-10; https://doaj.org/toc/2708-9967; https://doaj.org/toc/2708-9975

Zugangs-URL: https://doaj.org/article/c7def90be053473f9b38b0e68ab1afce

Employment of a Radial Basis Function Model for Predicting the Heating Load of Construction

Autoren: Yuxuan Dai

Quelle: Journal of Applied Science and Engineering, Vol 28, Iss 12, Pp 2315-2328 (2025)

Schlagwörter: heating load, heating energy consumption, radial basis function, populationbased vortex search algorithm, improved manta-ray foraging optimizer, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Physics, QC1-999

Dateibeschreibung: electronic resource

Relation: http://jase.tku.edu.tw/articles/jase-202512-28-12-0001; https://doaj.org/toc/2708-9967; https://doaj.org/toc/2708-9975

Zugangs-URL: https://doaj.org/article/991376e8935c4ce796b8d77148b37775

Improving the selection of differential evolution through a quartile-based ranked operator.

Autoren: Haro, Eduardo H. Oliva, Diego Casas-Ordaz, Angel et al.

Quelle: International Journal of Machine Learning & Cybernetics; Apr2025, Vol. 16 Issue 4, p2567-2602, 36p

Utilizing meta-heuristic algorithms for load-bearing capacity prediction in piles with support vector regression.

Autoren: Xu, Mengran Zhu, Zhihui

Quelle: Multiscale & Multidisciplinary Modeling, Experiments & Design; Nov2024, Vol. 7 Issue 5, p5445-5459, 15p

Gasification process modelling and optimization using Gaussian process regression and hybrid population-based algorithms.

Autoren: Si, Hongying

Quelle: Multiscale & Multidisciplinary Modeling, Experiments & Design; Sep2024, Vol. 7 Issue 4, p4151-4171, 21p

Improved multi-strategy artificial rabbits optimization for solving global optimization problems.

Autoren: Wang, Ruitong Zhang, Shuishan Jin, Bo

Quelle: Scientific Reports; 8/7/2024, Vol. 14 Issue 1, p1-22, 22p

Prediction of pile settlement by using hybrid random forest models.

Autoren: Yu, Shengnan

Quelle: Multiscale & Multidisciplinary Modeling, Experiments & Design; Jul2024, Vol. 7 Issue 3, p2087-2101, 15p

Having Deep Investigation on Predicting Unconfined Compressive Strength by Decision Tree in Hybrid and Individual Approaches.

Autoren: Qingqing Zhang Lei Wang Hongmei Gu

Quelle: International Journal of Advanced Computer Science & Applications; Jul2024, Vol. 15 Issue 7, p127-139, 13p

Predictive Modeling of Student Performance Through Classification with Gaussian Process Models.

Autoren: Xiaowei ZHANG Junlin YUE

Quelle: International Journal of Advanced Computer Science & Applications; Jun2024, Vol. 15 Issue 6, p1214-1227, 14p