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Predicting Stock Prices Using Machine Learning Methods and Deep Learning Algorithms: The Sample of the Istanbul Stock Exchange
(Gazi Univ, 2021)
Stock market prediction in financial and commodity markets is a major challenge for speculators, investors, and companies but also profitable with an accurate prediction. Thus, obtaining accurate prediction results becomes ...
A robust data simulation technique to improve early detection performance of a classifier in control chart pattern recognition systems
(Elsevier Science Inc, 2021)
The quality control process is essential in maintaining the stability of production systems and proactively detecting abnormalities that may result in high mechanical and labor costs. In this study, a new data simulation ...
A reduced variance unsupervised ensemble learning algorithm based on modern portfolio theory
(Pergamon-Elsevier Science Ltd, 2021)
Unsupervised ensemble learning or consensus clustering has gained popularity due to its ability to combine multiple clustering solutions into a single solution that is robust and often performs better than the individual ...
Cost-oriented LSTM methods for possible expansion of control charting signals
(Pergamon-Elsevier Science Ltd, 2021)
Manual quality control may result in delayed detection of a system defect, or none at all, potentially resulting in malfunctions that can lead to disruption of the system, incur extra costs, or complete downtime of the ...
Detection of damaged buildings after an earthquake with convolutional neural networks in conjunction with image segmentation
(Springer, 2021)
Detecting damaged buildings after an earthquake as quickly as possible is important for emergency teams to reach these buildings and save the lives of many people. Today, damaged buildings after the earthquake are carried ...