بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
forest algorithm » firefly algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
element » elements (توسيع البحث)
update » updated (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
forest algorithm » firefly algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
element » elements (توسيع البحث)
update » updated (توسيع البحث)
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
منشور في 2021"…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …"
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
منشور في 2022"…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …"
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masterThesis -
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Bird’s Eye View feature selection for high-dimensional data
منشور في 2023"…However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. …"
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
منشور في 2021الموضوعات: -
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Using genetic algorithms to optimize software quality estimation models
منشور في 2004"…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …"
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masterThesis -
31
Second-order conic programming for data envelopment analysis models
منشور في 2022"…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …"
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Analyzing the Influence of Climate and Anthropogenic Development on Vegetation Cover in the Coastal Ecosystems of GCC
منشور في 2025"…We used Landsat satellite imagery and a Random Forest classification algorithm to map various land cover classes along the GCC coastline. …"
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
منشور في 2023"…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. …"
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
منشور في 2024احصل على النص الكامل
doctoralThesis -
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
منشور في 2024"…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …"
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
منشور في 2022"…<p dir="ltr">Pressure gradient (PG) in liquid-liquid flow is one of the key components to design an energy-efficient transportation system for wellbores. This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …"
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An ant colony optimization algorithm to improve software quality prediction models
منشور في 2011"…For this purpose, software quality prediction models have been extensively used. However, building accurate prediction models is hard due to the lack of data in the domain of software engineering. …"
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
منشور في 2010"…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…"
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Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr...
منشور في 2020"…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …"
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