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modeling algorithm » scheduling algorithm (Expand Search)
mold algorithm » mould algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
mold algorithm » mould algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…<p dir="ltr">Development and modeling of proton exchange membrane fuel cells (PEMFCs) need accurate identification of unknown factors affecting mathematical models. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…<p>Machine learning algorithms have been intensively applied to perform load forecasting to obtain better accuracies as compared to traditional statistical methods. …”
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Development of a cerebral aneurysm segmentation method to prevent sentinel hemorrhage
Published 2023“…The proposed algorithm is tested on Three-Dimensional Rotational Angiography (3DRA) datasets; the average values of segmentation accuracy, DSC, FPR, FNR, specificity, and sensitivity, are found to be 99.72%, 93.52%, 0.07%, 5.23%, 94.77%, and 99.96%, respectively.…”
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Practical Multiple Node Failure Recovery in Distributed Storage Systems
Published 2016“…The fractional repetition (FR) code is a class of regenerating codes that consists of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …”
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conferenceObject -
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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…Every communication body wants to secure their data while communicating over the Internet. The internet has various benefits but the main demerit is the privacy and security and the transmission of data over insecure network or channel may happen. …”
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Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing
Published 2015Get full text
doctoralThesis -
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3D GEOSTATISTICAL MODELING OF FACIES AND PETROPHYSICAL PROPERTIES OF THE UPPER KHARTAM OUTCROP OF KHUFF FORMATION, CENTRAL SAUDI ARABIA
Published 2020“…In the context of 3D modelling, lithofacies within each zone was populated separately by using different geostatistical algorithm. …”
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Using artificial bee colony to optimize software quality estimation models. (c2015)
Published 2016“…Such models are mainly constructed by either statistical techniques such as regression, or machine learning techniques such as C4.5 and neural networks. …”
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masterThesis -
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Robust Kalman filter and smoother for errors-in-variables model with observation outliers based on Least-Trimmed-Squares
Published 2020“…Keywords: Errors-in-variables model, Least-Trimmed- Squares, Kalman filter and smoother, outliers, random search algorithm, subsampling method.…”
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Stability improvement of the PSS-connected power system network with ensemble machine learning tool
Published 2022“…The backtracking search algorithm (BSA) based proposed ensemble model is formed by combining three machine learning (ML) techniques, namely the extreme learning machine (ELM), neurogenetic (NG) system, and multi-gene genetic programming (MGGP). …”
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Novel hybrid informational model for predicting the creep and shrinkage deflection of reinforced concrete beams containing GGBFS
Published 2022“…Several statistical metrics, including the root mean square error and the coefficient of variation, revealed that the generalized model achieved the most reliable and accurate prediction of the concrete beam’s deflection in comparison with international standards and other models. …”
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A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns
Published 2023“…With the Gaussian Process regression for M2, the evaluation metrics for the PG prediction were found to be 10.65%, 86.26 Pa/m, and 0.96 for MAPE, root mean square error, and adjusted coefficient of determination, respectively. Statistical analysis showed that the selected features for liquids' and pipe's properties using the BGWOPSO algorithm were adequate to attain superior performance for both models. …”
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Integrated whole transcriptome and small RNA analysis revealed multiple regulatory networks in colorectal cancer
Published 2021“…Additionally, potential interaction between differentially expressed lncRNAs such as H19, SNHG5, and GATA2-AS1 with multiple miRNAs has been revealed. Taken together, our data provides thorough analysis of dysregulated protein-coding and non-coding RNAs in CRC highlighting numerous associations and regulatory networks thus providing better understanding of CRC.…”
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. …”
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