22   Artículos

 
en línea
Yu Yao and Quan Qian    
We develop the online process parameter design (OPPD) framework for efficiently handling streaming data collected from industrial automation equipment. This framework integrates online machine learning, concept drift detection and Bayesian optimization t... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Reenu Mohandas, Mark Southern, Eoin O?Connell and Martin Hayes    
Deep learning based visual cognition has greatly improved the accuracy of defect detection, reducing processing times and increasing product throughput across a variety of manufacturing use cases. There is however a continuing need for rigorous procedure... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Abdul Rehman Khalid, Nsikak Owoh, Omair Uthmani, Moses Ashawa, Jude Osamor and John Adejoh    
In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. This paper delves into the application of machine learning models, specifically focusing on ensemble met... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Abishek Manikandaraja, Peter Aaby and Nikolaos Pitropakis    
Artificial intelligence and machine learning have become a necessary part of modern living along with the increased adoption of new computational devices. Because machine learning and artificial intelligence can detect malware better than traditional sig... ver más
Revista: Computers    Formato: Electrónico

 
en línea
Guilherme Yukio Sakurai, Jessica Fernandes Lopes, Bruno Bogaz Zarpelão and Sylvio Barbon Junior    
The stream mining paradigm has become increasingly popular due to the vast number of algorithms and methodologies it provides to address the current challenges of Internet of Things (IoT) and modern machine learning systems. Change detection algorithms, ... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Michael Wood, Emanuele Ogliari, Alfredo Nespoli, Travis Simpkins and Sonia Leva    
Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics and... ver más
Revista: Forecasting    Formato: Electrónico

 
en línea
Antonio Maci, Alessandro Santorsola, Antonio Coscia and Andrea Iannacone    
Web phishing is a form of cybercrime aimed at tricking people into visiting malicious URLs to exfiltrate sensitive data. Since the structure of a malicious URL evolves over time, phishing detection mechanisms that can adapt to such variations are paramou... ver más
Revista: Computers    Formato: Electrónico

 
en línea
Juncal Alonso, Leire Orue-Echevarria, Eneko Osaba, Jesús López Lobo, Iñigo Martinez, Josu Diaz de Arcaya and Iñaki Etxaniz    
The current IT market is more and more dominated by the ?cloud continuum?. In the ?traditional? cloud, computing resources are typically homogeneous in order to facilitate economies of scale. In contrast, in edge computing, computational resources are wi... ver más
Revista: Information    Formato: Electrónico

 
en línea
Arvind Kumar Gangwar, Sandeep Kumar and Alok Mishra    
The early and accurate prediction of defects helps in testing software and therefore leads to an overall higher-quality product. Due to drift in software defect data, prediction model performances may degrade over time. Very few earlier works have invest... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Mashail Shaeel Althabiti,Manal Abdullah     Pág. pp. 90 - 106
Data stream is the huge amount of data generated in various fields, including financial processes, social media activities, Internet of Things applications, and many others. Such data cannot be processed through traditional data mining algorithms due to ... ver más

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