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sample processing » image processing (Expand Search), melt processing (Expand Search)
method algorithm » mould algorithm (Expand Search)
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241
A Multi-Channel Convolutional Neural Network approach to automate the citation screening process
Published 2021“…This study aims to automate the citation screening process using Deep Learning algorithms. With this, it is aimed to reduce the time and costs of the citation screening process and increase the precision and recall of the relevant primary studies. …”
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242
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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243
Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
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244
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. …”
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245
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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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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248
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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250
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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251
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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252
Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
Published 2024“…The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …”
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253
KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…Several techniques have been proposed in the literature to add some semblance of balance to the data sets by adding artificial data points. Synthetic Minority Oversampling Technique(SMOTE) and Adaptive Synthetic Sampling(ADASYN) are some of the commonly used techniques to deal with class imbalance. …”
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254
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255
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
Published 2017Get full text
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256
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257
Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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A Low-Cost Closed-Loop Solar Tracking System Based on the Sun Position Algorithm
Published 2019“…In contrast, the sun position algorithms use mathematical formula or astronomical data to obtain the station of the sun at a particular geographical location and time. …”
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260
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. …”