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research algorithm » search algorithm (Expand Search)
developing based » developing a (Expand Search), developing 21st (Expand Search)
using algorithm » cosine algorithm (Expand Search)
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281
Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development
Published 2025“…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”
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284
SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
Published 2018“…Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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287
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Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks
Published 2013“…In the proposed approach, mobiles are grouped into collaborative clusters using a low-complexity clustering algorithm. In each cluster, collaboration is implemented by having a cluster head send the content to other cluster members using a short-range wireless communications technology. …”
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289
Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
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290
A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…To show the applicability of the proposed approach, Iran’s bitumen consumption data in the period of 1991-2006 are used as a case study. …”
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Development of multivariable PID controller gains in presence of measurement noise
Published 2017“…The development of the proposed optimal algorithm is based on minimising a stochastic performance index in presence of erroneous initial conditions, white measurement noise, and white process noise. …”
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293
Performance evaluation of load balancing algorithms for parallel single-phase iterative PDE solvers
Published 1994“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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294
Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
Published 2003“…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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295
Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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296
Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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297
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”
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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …”
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KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. However, if the training data is not balanced among different classes, the performance of ML models deteriorate heavily. …”