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developing ii » developing a (Expand Search), developing _ (Expand Search)
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element » elements (Expand Search)
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101
A hybrid graph representation for recursive backtracking algorithms
Published 2017“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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conferenceObject -
102
Multiobjective evolutionary algorithms for electric power dispatch problem
Published 2006Get full text
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article -
103
Parallel Algorithms for Distinguishing Nondeterministic Finite State Machines
Published 2015Get full text
doctoralThesis -
104
Intelligent Rapidly-Exploring Random Tree Star Algorithm
Published 2024Get full text
doctoralThesis -
105
Formal synthesis of VLSI layouts from algorithmic specifications
Published 2020Get full text
article -
106
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107
Social spider optimization algorithm: survey and new applications
Published 2024“…This algorithm has been developed over time, resulting in many versions besides theories and findings. …”
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108
Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get full text
doctoralThesis -
109
Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers
Published 2024“…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …”
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110
Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…The objective of this thesis is to propose a methodology to apply ensembling in the detection of infected hosts considering these two aspects. As a function of the proposed objective, ensembling algorithms applicable to network security have been investigated and evaluated, and a methodology for detecting infected PAGE 2 hosts using ensembling has been developed, based on experiments designed and tested with real datasets. …”
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111
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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112
Developing an online hate classifier for multiple social media platforms
Published 2020“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”
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113
Big Data Energy Management, Analytics and Visualization for Residential Areas
Published 2020“…To achieve this, two big data processing paradigms are evaluated with a set of qualitative and quantitative metrics with subsequent recommendations. …”
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article -
114
Design and development of an embedded controller for roboticmanipulator
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article -
115
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116
Using genetic algorithms to optimize software quality estimation models
Published 2004“…Assessing software quality is fundamental in the software developing field. Most software quality characteristics cannot be measured before a certain period of use of the software product. …”
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masterThesis -
117
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
Published 2022Get full text
doctoralThesis -
118
An efficient approach for textual data classification using deep learning
Published 2022“…Textual data contains much useless information that must be pre-processed. …”
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119
Bee colony algorithm for assigning proctors to exams. (c2013)
Published 2013Get full text
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masterThesis -
120
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…The proposed method, named Eye-means, emulates the natural ocular process of estimating initial centroids. To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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masterThesis