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processing algorithm » processing algorithms (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
level using » level fusion (Expand Search)
text » test (Expand Search)
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv...
Published 2019“…The investigation that involves analysis and comparison is done for obtaining reduced total harmonic distortion (THD) by using different level-shifted multicarrier SPWM schemes along with proposed GA-based SHE. …”
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Land Use/Land Cover Changes Impact on Groundwater Level and Quality in the Northern Part of the United Arab Emirates
Published 2020“…This study aims to develop an integrated approach for mapping and monitoring land use/land cover (LULC) changes and to investigate the impacts of LULC changes and population growth on groundwater level and quality using Landsat images and hydrological information in a Geographic information system (GIS) environment. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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25
Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…According to the findings of several studies, the framework is significantly more effective than conventional methods in maintaining high levels of privacy. In addition, the framework outperforms conventional detection algorithms in words of detection rate, the rate of the false positive, and calculation time, respectively.…”
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26
A Neuro-Heuristic Approach for Segmenting Handwritten Arabic Text
Published 2001“…A conventional algorithm is used for the initial segmentation of the text into connected blocks of characters. …”
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Supervised term-category feature weighting for improved text classification
Published 2022“…Text classification is a central task in Natural Language Processing (NLP) that aims at categorizing text documents into predefined classes or categories. …”
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
Published 2021“…A machine learning classification pipeline is developed using multi-domain feature extraction (time, frequency, time-frequency), feature selection (Gini impurity), classifier design, and score level fusion. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…The application of DL to cyberbullying detection problems within Arabic text classification can be considered a novel approach due to the complexity of the problem and the tedious process involved, besides the scarcity of relevant research studies.…”
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An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm
Published 2021“…Second, a feature level fusion approach is used to combine the features. …”
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Activity-level space scheduling
Published 1992“…Its output layouts can be used to refine individual robot's trajectories using traditional path-planning algorithms.…”
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A neuro-heuristic approach for segmenting handwritten Arabic text. (c2001)
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Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms
Published 2022“…This was displayed the return of the portfolio produced using the DEA-Mean-CVaR model increased because the investment proposal was basedon the stock with the highest expected return and was effective at three risk levels. …”
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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…Maximum Absolute Difference (MAD), a new metric, that calculates the maximum absolute difference between simulated and measured hourly indoor temperatures, Root Mean Square Error (RMSE), Normalized Mean Bias Error (NMBE) were used as the evaluation criteria. Another new metric is introduced, 1 ◦C Percentage Error criterion that calculates the percentage of the number of hours with an error over 1 ◦C during the cali bration period, to select the best solutions from the Pareto Front solutions. 0.5 ◦C Percentage Error criterion is also used for the level of accuracy the model can achieve. …”
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Topics in graph algorithms
Published 2003“…This is a notable improvement over the previous best known algorithm, which runs in O(8kn). In addition to the structural and algorithmic results, this text tries to illustrate the practicality of fixed-parameter algorithms. …”
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Parallel implementation of clique partitioning using artificial neural networks. (c2000)
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40