بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
testing algorithm » cosine algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
data testing » data using (توسيع البحث)
element » elements (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
testing algorithm » cosine algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
data testing » data using (توسيع البحث)
element » elements (توسيع البحث)
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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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احصل على النص الكامل
masterThesis -
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Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations
منشور في 1992"…Three optimization methods derived from natural sciences are considered for allocating data to multicomputer nodes. These are simulated annealing, genetic algorithms and neural networks. …"
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
منشور في 2021"…A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …"
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
منشور في 2020"…An IEEE standard test system is used as the hybrid AC/DC microgrid case study to assess the performance of proposed model.…"
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KNNOR: An oversampling technique for imbalanced datasets
منشور في 2021"…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …"
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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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احصل على النص الكامل
masterThesis -
56
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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A reduced model for phase-change problems with radiation using simplified PN approximations
منشور في 2025"…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …"
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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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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
منشور في 2016"…Then, it searches for population discriminative motifs or differentiable sequence of SNPs, by implementing Probabilistic Suffix Trees data structures. We initially tested the efficiency and performance of our method on several simulated datasets and then applied it on a real genomic data that has different populations from the Middle East and North Africa (MENA) region. …"
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احصل على النص الكامل
masterThesis -
60
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. …"