Search Results - subject_exact:"Mustererkennung"

Short-term forecasting of four Rand-denominated currency markets (EUR/ZAR, CHF/ZAR, BRL/ZAR, CNY/ZAR) : a comparative analysis of Support Vector Regression, XGBoost and Principal Component Regression

Fundama, Sthembile Albertinah; Ravele, Thakhani; … - 2026

Using daily data from Investing.com South Africa, this study investigates the forecasting performance of four Rand currency rate markets (EUR/ZAR, CHF/ZAR, BRL/ZAR, and CNY/ZAR) from 13 February 2018 until 24 February 2025. The predictive fitness of three competing models, Support Vector...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015656136

AI-driven bankruptcy prediction in manufacturing SMEs : comparing machine learning techniques with logistic regression

Letkovský, Stanislav; Jenčová, Sylvia; … - 2026

Bankruptcy prediction is currently a widely researched topic, as it typically results from a chain of negative events. Logistic Regression (LR) is one of the standard prediction tools; however, with advances in technology, machine learning (ML) methods are gaining prominence and demonstrating...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015634019

Intelligent policy framework : natural resource conservation, knowledge and big data analytics

Xiao, Nina; Qu, Xianhe - 2025

In today's context of escalating environmental pressure, traditional methods of natural resource conservation face numerous challenges. The use of big data analytics to support the formulation of environmental policies has become a crucial approach for enhancing the efficiency and scientific...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015331637

A machine learning approach for text pattern diagnosis in mental health consultations

Juanita, Safitri; Daeli, Anisah Hasratniwati; … - 2025

Online health consultation services are crucial for mental health support, particularly in densely populated areas. However, the heavy reliance on human expertise often leads to delays, necessitating more efficient and automated solutions. This study developed a machine learning framework to...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015420451

A novel robust optimization model for nonlinear Support Vector Machine

Maggioni, Francesca; Spinelli, Andrea - 2025

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015410212

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

Farag, Karim; Ali, Loubna; Mutai, Noah Cheruiyot; … - 2025

There is an ongoing debate about the role of income diversification in enhancing bank stability within the financial services industry in Europe. Some advocate for diversification, while others argue that its importance should not be overstated. Some financial institutions are encouraged to...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015432827

A robust support vector machine approach for Raman data classification

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

Recent advances in healthcare technologies have led to the availability of large amounts of biological samples across several techniques and applications. In particular, in the last few years, Raman spectroscopy analysis of biological samples has been successfully applied for early-stage...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015506507

Machine learning applications in finance : special issue reprint

2025 - 2nd edition

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015609822

Forecasting macro with finance

Bachmair, Kilian; Schmitz, Niklas - 2025

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015651405

Development of a preprocessing methodology for imbalanced datasets in machine learning training

Zlobin, Mykola; Bazylevych, Volodymyr - 2025

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015666419

Forecasting relative returns for S&P 500 stocks using machine learning

Htet Htet Htun; Biehl, Michael; Petkov, Nicolai - 2024

Forecasting changes in stock prices is extremely challenging given that numerous factors cause these prices to fuctuate. The random walk hypothesis and efcient market hypothesis essentially state that it is not possible to systematically, reliably predict future stock prices or forecast changes...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014547210

A performance analysis of stochastic processes and machine learning algorithms in stock market prediction

Bouasabah, Mohammed - 2024

In this study, we compare the performance of stochastic processes, namely, the Vasicek, Cox-Ingersoll-Ross (CIR), and geometric Brownian motion (GBM) models, with that of machine learning algorithms, such as Random Forest, Support Vector Machine (SVM), and k-Nearest Neighbors (KNN), for...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015070753

A novel fusion Support Vector Machine integrating weak and sphere models for classification challenges with massive data

Pimentel, Jonatha Sousa; Ospina, Raydonal; Ara, Anderson - 2024

The unprecedented growth in data generation has necessitated the adoption of advanced analytical techniques. Support Vector Machine (SVM) is a powerful machine learning tool that has proven invaluable in classifying observations through optimal hyperplane in higher dimensions. Despite their...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015101975

The volatility mechanism and intelligent fusion forecast of new energy stock prices

Fan, Guo-Feng; Zhang, Ruo-Tong; Cao, Cen-Cen; Peng, Li-Ling - 2024

The new energy industry is strongly supported by the state, and accurate forecasting of stock price can lead to better understanding of its development. However, factors such as cost and ease of use of new energy, as well as economic situation and policy environment, have led to continuous...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014535574

A hybrid model for stock price prediction based on multi-view heterogeneous data

Long, Wen; Gao, Jing; Bai, Kehan; Lu, Zhichen - 2024

Literature shows that both market data and fnancial media impact stock prices; however, using only one kind of data may lead to information bias. Therefore, this study uses market data and news to investigate their joint impact on stock price trends. However, combining these two types of...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014536032

Digital identification and pattern recognition capabilities using machine learning methods, navigation systems, and video surveillance

Marchenko, Olena; Viunenko, Oleksandr; Nechai, Ihor - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014497309

Convex support vector regression

Liao, Zhiqiang; Dai, Sheng; Kuosmanen, Timo - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014456645

Comparison of improved relevance vector machines for streamflow predictions

Adnan, Rana Muhammad; Mostafa, Reham R.; Dai, Hong-Liang; … - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014443193

Mixed-integer quadratic optimization and iterative clustering techniques for semi-supervised support vector machines

Burgard, Jan Pablo; Pinheiro, Maria Eduarda; Schmidt, Martin - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015188200

Adapting support vector optimisation algorithms to textual gender classification

Gomez, Javier; Alfaro, Cesar; Ortega, Felipe; Moguerza, … - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015188211

Machine learning methods for financial forecasting and trading profitability : evidence during the Russia-Ukraine war

Peng, Yaohao; Souza, João Gabriel de Moraes - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015189762

Modeling the effect of population size on banking transaction channels in Nigeria : Grey box vs Support Vector Regression

Bartholomew, Desmond C.; Olewuezi, Ngozi P.; Nwaigwe, … - 2024

This study investigates the effect of Nigeria's population on four selected banking transaction channels. The Nigerian projected population (2022-2027) was used as an input variable for forecasting future volumes of transactions for each channel. The results show that the Support Vector...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015393855

Intellectual capital forecasting for invention patent through machine learning model

Wang, Mei-Hsin; Che, Hui-Chung - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015419528

Application of artificial intelligence data mining algorithm in enterprise management risk assessment

Zhu, Juntao - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015433098

Construction of a multimedia instructional effect assessment system of college foreign language translation based on artificial intelligence

Liu, Shuang; Yi, Man - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015433110

Nowcasting GDP: what are the gains from machine learning algorithms?

Arro-Cannarsa, Milen; Scheufele, Rolf - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015044842

Novel comparative methodology of hybrid support vector machine with meta-heuristic algorithms to develop an integrated candlestick technical analysis model

Mahmoodi, Armin; Hashemi, Leila; Mahmoodi, Amin; … - 2024

Purpose The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM),...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015047541

Identifying marriage markets

Bolletta, Ugo; Cherchye, Laurens; Demuynck, Thomas; … - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015050255

A hybrid model for forecasting realized volatility based on heterogeneous autoregressive model and support vector regression

Zhuo, Yue; Morimoto, Takayuki - 2024

In this study, we proposed two types of hybrid models based on the heterogeneous autoregressive (HAR) model and support vector regression (SVR) model to forecast realized volatility (RV). The first model is a residual-type model, where the RV is first predicted using the HAR model, and the...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014480965

Margin optimal classification trees

D'Onofrio, Federico; Grani, Giorgio; Monaci, Marta; … - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014559221

Financial distress prediction using artificial neural network partial least squares regression support vector machine hybrid model and logit model

Osoolian, Mohammad; Varahrami, Vida; Razavi, Hoda - 2024

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015402991

Computer Vision in Healthcare : Prediction, Detection and Diagnosis

2026 - First edition

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015589355

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

Kakhki, Hossein Alaee; Saghih, Amir Mohammad Fakoor; … - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015627357

The role of artificial intelligence in shaping entrepreneurial consumer behavior

Ahmed, Rizwan Raheem; Anwar, Rana Salman; … - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015647320

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

Soltani, Azadeh; Nikkhah-Farkhani, Zahra - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015632065

Corrected support vector regression for intraday point forecasting of prices in the continuous power market

Puć, Andrzej; Janczura, Joanna - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015668483

A Hybrid Forecasting Method for Anticipating Stock Market Trends via a Soft- Thresholding De-noise Model and Support Vector Machine (SVM)

Zhang, Lixuan; Li, Chang; Chen, Lee; Chen, Don; Xiang, Zheng - 2023

Stock market time series are inherently noisy. Although support vector machine has the noise-tolerant property, the noised data still affect the accuracy of classification. Compared with other studies only classify the movements of stock market into up-trend and down-trend which does not concern...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014351174

Prediction of corporate credit ratings with machine learning : simple interpretative models

Galil, Koresh; Hauptman, Ami; Rosenboim, Rosit Levy - 2023

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014634152

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

Breast cancer is the most common life-threatening cancer in women and one of the leading causes of death. Early diagnosis is one of the best defenses against the spread of breast cancer. Machine learning (ML) tools are now available for cancer detection and prediction. This study presents a...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014497358

An unsupervised learning-based generalization of Data Envelopment Analysis

Moragues, Raul; Aparicio, Juan; Esteve, Miriam - 2023

In this paper, we introduce an unsupervised machine learning method for production frontier estimation. This new approach satisfies fundamental properties of microeconomics, such as convexity and free disposability (shape constraints). The new method generalizes Data Envelopment Analysis (DEA)...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014448520

Is artificial intelligence really more accurate in predicting bankruptcy?

Letkovský, Stanislav; Jeňcová, Sylvia; … - 2023

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, ebvufind01.dmz1.zbw.eu/10014502270

A comparative study of statistical machine learning methods for condition monitoring of electric drive trains in supply chains

Lahmiri, Salim - 2023

Fault detection and identification are critical for the accurate maintenance and management of industrial machinery. In this regard, data-driven condition monitoring models play an important role in machinery fault diagnosis and management. This study investigates the applicability of various...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014516481

Application of support vector machine algorithm for early differential diagnosis of prostate cancer

Akinnuwesi, Boluwaji A.; Olayanju, Kehinde A.; … - 2023

Prostate cancer (PCa) symptoms are commonly confused with benign prostate hyperplasia (BPH), particularly in the early stages due to similarities between symptoms, and in some instances, underdiagnoses. Clinical methods have been utilized to diagnose PCa; however, at the full-blown stage, clinical...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014517987

Forecasting stock closing prices with an application to airline company data

Xu, Xu; Zhang, Yixiang; McGrory, Clare Anne; Wu, Jinran; … - 2023

Forecasting stock market movements is a challenging task from the practitioners' point of view. We explore how model selection via the least absolute shrinkage and selection operator (LASSO) approach can be better used to forecast stock closing prices using real-world datasets of daily stock...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014518025

A novel approach for candlestick technical analysis using a combination of the support vector machine and particle swarm optimization

Mahmoodi, Armin; Hashemi, Leila; Jasemi, Milad; … - 2023

Purpose - In this research, the main purpose is to use a suitable structure to predict the trading signals of the stock market with high accuracy. For this purpose, two models for the analysis of technical adaptation were used in this study. Design/methodology/approach - It can be seen that...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10014309150