Search Results - subject:"Support Vector Machine"

Strategic taxonomy of supply chain sustainability in manufacturing companies : evidence from Iran

Kakhki, Hossein Alaee; Saghih, Amir Mohammad Fakoor; … - In: International journal of logistics systems and … 53 (2026) 1, pp. 69-92

Persistent link: https://www.econbiz.de/10015627357

Innovative behaviour forecasting : assessment of the impact of organisational intelligence factors

Soltani, Azadeh; Nikkhah-Farkhani, Zahra - In: International journal of productivity and quality … 47 (2026) 1, pp. 38-53

Persistent link: https://www.econbiz.de/10015632065

The role of artificial intelligence in shaping entrepreneurial consumer behavior

Ahmed, Rizwan Raheem; Anwar, Rana Salman; … - In: International entrepreneurship and management journal 22 (2026) 1, pp. 1-32

Persistent link: https://www.econbiz.de/10015647320

Prediction and analysis of customer complaints using machine learning techniques

Alarifi, Ghadah; Rahman, Mst Farjana; Hossain, Md Shamim - In: International journal of e-business research : IJEBR ; … 19 (2023) 1, pp. 1-25

Persistent link: https://www.econbiz.de/10015051113

Forecasting stock closing prices with an application to airline company data

Xu, Xu; Zhang, Yixiang; McGrory, Clare Anne; Wu, Jinran; … - In: Data science and management : DSM 6 (2023) 4, pp. 239-246

also compare our approach with ridge, tree, and support vector machine regressions, as well as neural network approaches to …

Persistent link: https://www.econbiz.de/10014518025

Is artificial intelligence really more accurate in predicting bankruptcy?

Letkovský, Stanislav; Jeňcová, Sylvia; … - In: International Journal of Financial Studies : open … 12 (2024) 1, pp. 1-19

Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial intelligence (AI) has shown high success...

Persistent link: https://www.econbiz.de/10014502270

A comparative assessment of machine learning algorithms with the Least Absolute Shrinkage and Selection Operator for breast cancer detection and prediction

Hassan, Md. Mehedi; Hassan, Md. Mahedi; Yasmin, Farhana; … - 2023

Boosting (XGB), Gradient Boosting (GB), Random Forest (RF), Multilayer Perceptron (MLP), and Support Vector Machine (SVM …

Persistent link: https://www.econbiz.de/10014497358

Evaluation and analysis of classroom teaching quality of art design specialty based on DBT-SVM

Guo, Junmei - In: International journal of networking and virtual … 28 (2023) 2/4, pp. 106-121

Persistent link: https://www.econbiz.de/10014435575

A robust support vector machine approach for Raman data classification

Piazza, Marco; Spinelli, Andrea; Maggioni, Francesca; … - 2025

Vector Machine (SVM) in classifying COVID-19 samples obtained from Raman spectroscopy. Given the noisy and perturbed nature … predictive models under data uncertainty. In this paper, we investigate the performance of a novel robust formulation for Support …

Persistent link: https://www.econbiz.de/10015506507

Machine learning for predicting bank stability : the role of income diversification in European banking

Farag, Karim; Ali, Loubna; Mutai, Noah Cheruiyot; … - In: FinTech 4 (2025) 2, pp. 1-19

fixed-effects model, with machine-learning algorithms such as Random Forest and Support Vector Machine. These methods are …

Persistent link: https://www.econbiz.de/10015432827