Search Results - property distribution ((mining algorithm) OR (learning algorithm))
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Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation
Published 2020“…The proposed algorithm named as Box-Whisker Data Transformation considered all samples contain in a MLCC dataset in order to generate artificial samples. …”
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Development of a new algorithm for segmentation of flotation froth images
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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Exploring The Synergy Of Template And Machine Learning Methods To Improve Photometric Redshifts
Published 2024“…The first method involves using template fitting to model the spectral energy distribution of a galaxy and estimate its redshift. The second method uses machine learning algorithms to learn the relationship between a galaxy’s photometric properties and its redshift, based on a training set of spectroscopic redshift measurements. …”
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Random sampling method of large-scale graph data classification
Published 2024“…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
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CFD modeling on coal properties towards the burnout efficiency
Published 2024text::Final Year Project -
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In supervised learning, class imbalanced data set is a state where the class distribution is not uniform among the classes. …”
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A lightweight graph-based pattern recognition scheme in mobile ad hoc networks.
Published 2012“…Its one-cycle learning and divide and distribute recognition task approach allows DHGN to detect similar patterns in short of time. …”
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A New Robust Weak Supervision Deep Learning Approach for Reservoir Properties Prediction in Malaysian Basin Field
Published 2023“…In this work, we develop a robust approach to deep learning-based seismic inversion to predict elastic properties from seismic data. …”
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Predictive Framework for Imbalance Dataset
Published 2012“…Experimental results suggested that the class probability distribution function of a prediction model has to be closer to a training dataset; less skewed environment enable learning schemes to discover better function F in a bigger Fall space within a higher dimensional feature space, data sampling and partition size is appear to proportionally improve the precision and recall if class distribution ratios are balanced. …”
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AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico Analysis
Published 2023“…By harnessing AI's virtuosity, drug discovery processes are imbued with unprecedented speed and precision. Machine learning algorithms harmonize with intricate biological datasets, unraveling patterns and relationships previously enshrouded in complexity. …”
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Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…These results show that,for all the arrays (2D and 3D) except 3D pole - dipole data, resilient propagation is the most efficient algorithm for training the DC resistivity data. In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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Software agent as an effective tool for managing the Internet of thing data complexity
Published 2017“…On top of that, the existing analysis tools and algorithms did not consider the data generated by sensory devices connected to the Internet. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The locations of landslides were detected accurately by employing two Machine learning classifiers, namely, SVM and RF, decision rule and hierarchal rules sets were developed by applying decision tree (DT) algorithm to provide improved landslide inventory. …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
Published 2019“…GMM could reproduce the slope angle distribution in an accurate way with a coefficient of determination close to 1. …”
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Development of an automated detector and counter for bagworm census
Published 2020“…The living and dead bagworm spectral reflectance properties were determined using spectroradiometer, GER1500 under the Visible/Near Infrared and Short-wave Infrared wavelength regions, 350 – 1050 nm, and the results were statistically confirmed using Student’s t- Test with two tailed distributions, principal component analysis and Boxplot Quantiles. …”
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