Search Results - (( ((pre processing) OR (data processing)) based algorithm ) OR ( java application bat algorithm ))
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The Design of Pre-Processing Multidimensional Data Based on Component Analysis
Published 2011“…RapidMiner is used for data pre-processing using FastICA algorithm. Kernel K-mean is used to cluster the pre-processed data and Expectation Maximization (EM) is used to model. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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Image Processing Of Digital Mammograms For Breast Cancer Detection And Classification
Published 2018“…The algorithms to be developed will consist of pre-processing, enhancement and image segmentation. …”
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Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons
Published 2018“…Relatively good performance of the proposed hybrid models with a data pre-processing approach provides a successful alternative to achieve better accuracy in streamflow forecasting compared to the traditional artificial neural network approach without a data pre-processing scheme.…”
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An efficient real-time terrain data organization and visualization algorithm based on enhanced triangle-based level of detail technique
Published 2006“…According to the results obtained during the pre-processing, the partitioning of digital elevation data into tiles has successfully reduced the data size although it required a longer processing time. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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Sizes of Superpixels and their Effect on Interactive Segmentation
Published 2021“…Pre-processing steps can be used to speed up the segmentation process while improving the end result. …”
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Sizes of Superpixels and their Effect on Interactive Segmentation
Published 2021“…Pre-processing steps can be used to speed up the segmentation process while improving the end result. …”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…Two different pre-processing scenarios were proposed to handle unstructured text data, one of the most challenging aspects of classifying text from social media. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…However, the choice of k is a prominent problem in the process of the k-means algorithm. In most cases, for clustering huge data, k is pre-determined by researchers and incorrectly chosen k, could end with wrong interpretation of clusters and increase computational cost. …”
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EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method
Published 2018“…The accuracy of ESL depends on all the stages of data processing including: head model reconstruction, signal pre-processing and inverse solution. …”
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Establishment of spectral subtraction-based algorithm for experimental modal analysis under operating condition
Published 2022“…The direction of ambient response at each frequency band was estimated based on the reconstructed artificial ambient. The artificial ambient was reproduced based on pre-triggered data in measured vibration response. …”
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Big Data Mining Using K-Means and DBSCAN Clustering Techniques
Published 2022“…Results obtained after pre-processing phase showed that the data quality will improve when the number of records reduced by (51.45). …”
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An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets
Published 2021“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For contextual text classification, the pre-trained LLM is further train on classificationspecific labeled data in a process called fine-tuning. …”
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