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Oversampling techniques for imbalanced data in regression
Published 2024“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”
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Development of an Optimization Algorithm for Internet Data Traffic
Published 2020“…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. …”
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UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks
Published 2018“…Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of Unmanned Aerial Vehicles (UAVs) to collect data in dense wireless sensor networks (WSNs) using projection-based Compressive Data Gathering (CDG) as a novel solution methodology. …”
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Energy-aware adaptive compression for mobile devices. (c2009)
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A Fuzzy Low-Dimensional Intersection Graph Representation Approach for Graph Compression and Anonymization
Published 2021“…The objective is to answer adjacency queries as accurately as possible and to achieve an effective compression. We examine several heuristic algorithms in an attempt to achieve these two main objectives and conduct a thorough experimental analysis providing evidence of the effectiveness of our graph mapping approach. …”
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
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Regression Testing of Database Applications
Published 2002“…This analysis leads to selecting test cases from the initial test suite for regression testing the modified application. In phase 2, further reduction in the regression test cases is performed by using reduction algorithms. …”
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Shuffled Linear Regression with Erroneous Observations
Published 2019“…Linear regression with shuffled labels is the problem of performing a linear regression fit on datasets whose labels are unknowingly shuffled with respect to their inputs. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
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An Alternating Projection Framework for Elementwise Masked Nonlinear Matrix Decomposition
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
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Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…An advanced seismic compression technique is proposed to manage seismic data in a world of ever increasing data volumes in order to maintain productivity without compromising interpretation results. …”
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