VM Migration and Resource Management using Meta Heuristic Technique in Cloud Computing Services DOI
Abhijit Kumar, Runumi Devi

Published: April 29, 2023

An increasingly important component in the development of Cloud Computing, an Internet-based technology, is optimization its resources. To make most available resources, cloud data centre models need a resource management strategy. The Bin-Packing issue combinatorial that may be used to efficiently assign virtual machines physical machines. In this study, we present two-stage approach for managing and allocating resources effectively. first step, propose Load Balanced Multi-Dimensional (LBMBP) heuristics (VMs) (PMs or hosts) by taking into account all at their disposal. As indicated second stage, technique identify overload load balance hosts based on anomalies necessary VM migration. CloudSim Plus Simulator simulation results were demonstrate planned work, it was found number operational PMs reduced. Reduced energy use emigration rates due more efficient

Language: Английский

Hybrid neural network-based metaheuristics for prediction of financial markets: a case study on global gold market DOI Creative Commons
Mobina Mousapour Mamoudan, Ali Ostadi, Nima Pourkhodabakhsh

et al.

Journal of Computational Design and Engineering, Journal Year: 2023, Volume and Issue: 10(3), P. 1110 - 1125

Published: April 29, 2023

Abstract Technical analysis indicators are popular tools in financial markets. These help investors to identify buy and sell signals with relatively large errors. The main goal of this study is develop new practical methods fake obtained from technical the precious metals market. In paper, we analyze these different ways based on recorded for 10 months. novelty research propose hybrid neural network-based metaheuristic algorithms analyzing them accurately while increasing performance indicators. We combine a convolutional network bidirectional gated recurrent unit whose hyperparameters optimized using firefly algorithm. To determine select most influential variables target variable, use another successful recently developed metaheuristic, namely, moth-flame optimization Finally, compare proposed models other state-of-the-art single deep learning machine literature. finding that metaheuristics can be useful as decision support tool address control enormous uncertainties

Language: Английский

Citations

42
Bio-inspired meta-heuristic algorithm for solving engineering optimization problems based on computational intelligence DOI

S. Saranya,

S. Mohanapriya,

Dinesh Komarasamy

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 259 - 280

Published: Jan. 1, 2025

Language: Английский

Citations

1
Sustainable supply chain decision-making in the automotive industry: A data-driven approach DOI

Hanieh Zareian Beinabadi,

Vahid Baradaran, Alireza Rashidi Komijan

et al.

Socio-Economic Planning Sciences, Journal Year: 2024, Volume and Issue: 95, P. 101908 - 101908

Published: May 23, 2024

Language: Английский

Citations

6
The financial impact of human resources configuration: A quantitative analysis based on modified single candidate optimizer DOI Creative Commons

Zhuozhuo Zhang,

Jun Lü, Yanyan Wang

et al.

Egyptian Informatics Journal, Journal Year: 2025, Volume and Issue: 29, P. 100584 - 100584

Published: Jan. 11, 2025

Language: Английский

Citations

0
Examining the application of strategic management and artificial intelligence, with a focus on artificial neural network modeling to enhance human resource optimization with advertising and brand campaigns DOI

Cao Ruoxing,

Wang Jian-ning,

Ali Basem

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 143, P. 110029 - 110029

Published: Jan. 21, 2025

Language: Английский

Citations

0
Inteligencia artificial en la mejora del talento humano y gestión del conocimiento en organizaciones: una revisión sistemática en Scopus DOI Creative Commons

J. Urbina

Revista Cientifica de Sistemas e Informatica, Journal Year: 2025, Volume and Issue: 5(1), P. e889 - e889

Published: Jan. 20, 2025

Este estudio analiza la aplicación de inteligencia artificial (IA) en gestión del talento humano y el conocimiento organizacional mediante una revisión sistemática 50 artículos científicos indexados Scopus. Se empleó metodología documental con criterios selección basados relevancia actualidad. identificaron las principales aplicaciones IA optimización procesos administrativos, personalización programas formación toma decisiones estratégicas basadas datos. Entre los enfoques analizados destacan aprendizaje automático, minería datos sistemas expertos, cuales han mejorado evaluación desempeño, personal conocimiento. Los resultados evidencian que ha incrementado eficiencia talento, aunque persisten desafíos como calidad datos, resistencia sesgos algoritmos selección. concluye adopción recursos humanos sigue crecimiento, promoviendo modelos más adaptativos. Sin embargo, es necesario abordar sus limitaciones marcos normativos estrategias supervisión garanticen implementación ética, equitativa alineada objetivos organizacionales.

Citations

0
Literature survey on combining machine learning and metaheuristics for decision-making DOI Open Access
A. V. Kharitonov,

Jonathan Ifeanyichukwu Abani,

Abdulrahman Nahhas

et al.

Procedia Computer Science, Journal Year: 2025, Volume and Issue: 253, P. 199 - 208

Published: Jan. 1, 2025

Language: Английский

Citations

0
CNN TABANLI DERİN ÖĞRENME VE MAKİNE ÖĞRENMESİ TEKNİKLERİNİN ENTEGRASYONU: İŞTEN AYRILMA TAHMİNLERİNDE YENİ BİR METODOLOJİ DOI
Yunus Emre Gür, Cem Ayden

International Journal of Management Economics and Business, Journal Year: 2025, Volume and Issue: 21(1), P. 161 - 198

Published: March 26, 2025

İşgücü devri, organizasyonlar için önemli maliyet ve verimlilik kayıplarına yol açmaktadır. Bu çalışma, işten ayrılma tahminlerini geliştirmek amacıyla, geleneksel istatistiksel modellerin ötesine geçerek makine öğrenimi derin öğrenme tekniklerini entegre eden yenilikçi bir yaklaşım sunmaktadır. Çalışma, veri setindeki değişkenleri 2B karekod görüntülerine dönüştürmek suretiyle, CNN tabanlı modellerinin bu görüntüler üzerinde sınıflandırma yapabilmesini sağlamıştır. adım, görsel işleme yeteneklerini kullanarak daha karmaşık yapılarını analiz etme potansiyelini ortaya koymaktadır. Araştırma, çeşitli öğrenmesi modellerini değerlendirdikten sonra ResNet-18 modeli kullanılarak özellik çıkarımı gerçekleştirilmiştir. Daha sonra, RelieF algoritması seçilen en etkili 10 özelliğe dayanarak optimize edilmiş Hafif Gradyan Artırma (LighhtGBM) modeli, %100 doğruluk, hassasiyet F1-skoru gibi mükemmel performans metrikleri elde etmiştir. sonuçlar, modelin tahminlerinde yüksek etkinlik sergilediğini insan kaynakları yönetimi pratiğine katkılarda bulunabileceğini göstermektedir.

Citations

0
The Role of Job Stability in Reducing Employee Turnover Rates in Nass Bahrain Company DOI
Marwan Milhem,

Ali Ateeq,

Noor Al-saffar

et al.

Studies in big data, Journal Year: 2025, Volume and Issue: unknown, P. 665 - 679

Published: Jan. 1, 2025

Language: Английский

Citations

0
Optimization Method for Human Resource Decision Based on Hadoop Big Data Platform DOI Open Access
Xueqi Zhang

Advances in transdisciplinary engineering, Journal Year: 2024, Volume and Issue: unknown

Published: June 26, 2024

When enterprises face a large amount of enterprise data, how to effectively utilize information better manage talent has become key issue that urgently needs be solved. Therefore, this article proposes human resource decision-making optimization method based on the Hadoop big data platform. By taking steps such as collection, feature extraction, model construction, and decision optimization, scientificity accuracy management can improved. This compares performance algorithm used with machine learning (ML) deep (DL) algorithms, results indicate F1 value designed in is 95.8%, which higher than 84.7% DL 77.9% ML. Experiments have shown enhance efficiency decision-making, providing strong support for enterprises.

Language: Английский

Citations

3