بدائل البحث:
processing algorithm » processing algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
settings » setting (توسيع البحث)
element » elements (توسيع البحث)
processing algorithm » processing algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
settings » setting (توسيع البحث)
element » elements (توسيع البحث)
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41
Web Based Online Hybrid Teaching Method of Network Music Course
منشور في 2022"…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …"
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42
Towards Scalable Process Mining Pipelines
منشور في 2023"…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …"
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43
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44
An ant colony optimization algorithm to improve software quality prediction models
منشور في 2011"…This is suitable for the domain of software quality since the data is very scarce and hence predictive models built from one data set is hard to generalize and reuse on new data.…"
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article -
45
Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
منشور في 2021احصل على النص الكامل
doctoralThesis -
46
An enhanced k-means clustering algorithm for pattern discovery in healthcare data
منشور في 2015"…The huge amounts of data generated by media sensors in health monitoring systems, by medical diagnosis that produce media (audio, video, image, and text) content, and from health service providers are too complex and voluminous to be processed and analyzed by traditional methods. …"
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article -
47
Mining airline data for CRM strategies. (c2006)
منشور في 2006احصل على النص الكامل
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masterThesis -
48
Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic
منشور في 2021"…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …"
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49
Nonlinear analysis of shell structures using image processing and machine learning
منشور في 2023"…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"
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50
Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
منشور في 2011"…The data was used as training and testing sets to analyze certain machine learning algorithms in terms of performance (cost / benefit analysis) and accuracy (mean error square and confusion matrix). …"
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51
UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks
منشور في 2018"…Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. …"
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article -
52
Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
منشور في 2018"…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …"
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masterThesis -
53
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54
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55
Software defect prediction. (c2019)
منشور في 2019احصل على النص الكامل
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masterThesis -
56
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57
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59
KNNOR: An oversampling technique for imbalanced datasets
منشور في 2021"…Several techniques have been proposed in the literature to add some semblance of balance to the data sets by adding artificial data points. Synthetic Minority Oversampling Technique(SMOTE) and Adaptive Synthetic Sampling(ADASYN) are some of the commonly used techniques to deal with class imbalance. …"
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60
Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
منشور في 2025"…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …"