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141
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…Unsupervised machine learning is a powerful technique for performing clustering, which involves identifying patterns or similarities within a dataset and grouping them into distinct clusters or subgroups. …”
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masterThesis -
142
Animal migration optimization algorithm: novel optimizer, analysis, and applications
Published 2024“…Optimization algorithms are applied to find the optimal solutions in many domains and fields such as image processing, machine learning, and others. …”
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143
Using genetic algorithms to optimize software quality estimation models
Published 2004“…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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masterThesis -
144
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145
Pre-production movie rating prediction using machine learning. (c2017)
Published 2017“…In this work, we present several machine learning techniques (Support Vectors Machine, K-Nearest Neighbors, C5, Neural Networks and Case-Based Reasoning) along with a genetic algorithm to predict the success of a movie before its production using the IMDB rating as an indicator of the success. …”
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masterThesis -
146
Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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147
Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta
Published 2023“…In this regard, our study aims to predict the permeability of molecules across the placental barrier. Based on publicly available datasets, several machine learning models are comprehensively analysed across different fingerprints and toolkits to find the best suitable models. …”
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148
Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants
Published 2022“…</p><p><br></p><h3>Methods</h3><p dir="ltr">We developed an XGBoost-based machine learning model to predict pathogenicity of BRCA2 variants. …”
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149
Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
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doctoralThesis -
150
FPGA-based Parallel Hardware Architecture for Real-time Object Classification
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doctoralThesis -
151
Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices
Published 2024“…Based on the performance metrics, such as confusion matrix, training time, prediction time, accuracy, and Area Under the Receiver Operating Characteristic curve (AUC-ROC), it was established that SDN-ML-IoT, when applied to RF, outperforms other ML algorithms, as well as similar approaches related to our work. …”
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152
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…Furthermore, more advanced algorithms can be used such as Support Vector machine (SVM) and XGBoost.…”
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153
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154
A method for optimizing test bus assignment and sizing for system-on-a-chip
Published 2017“…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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conferenceObject -
155
Assessment of static pile design methods and non-linear analysis of pile driving
Published 2006“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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masterThesis -
156
Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
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doctoralThesis -
157
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158
Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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159
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160
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…<p dir="ltr">Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. …”