Search Results - (( variable stacking based algorithm ) OR ( java adaptation optimization algorithm ))
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1
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
2
Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
Conference Paper -
3
A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction
Published 2024journal::journal article -
4
Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…Besides that, this study proposed two hybrid LSTM-GRU based models. The hybrid models were LSTM-GRU Double Stack(LGDS) and LSTM-GRU Alternate Double Stack (LGADS). …”
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5
Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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6
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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7
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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