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121
Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…Generally, RKPCA reduces the number of samples in the training data set and then builds the KPCA model based on this data set. …”
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122
A Framework for Predictive Modeling in Sustainable Projects
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123
NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…Various sensors and equipment are installed in the AAL context to collect a wide variety of data. Furthermore, AAL could be the motivating technique for the most recent care models by working as an adjunct. …”
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124
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
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Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development
Published 2025“…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …”
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129
A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading
Published 2020“…The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. The outcomes from the algorithm are based on clustering the solar insolation values and then applying a genetic algorithm optimisation to indicate the optimum BIPV array layout for maximum yield.…”
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130
A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. …”
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Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
Published 2019Get full text
doctoralThesis -
133
SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
Published 2018“…This paper describes SemIndex+, a semantic-aware indexing and querying framework that allows semantic search, result selection, and result ranking of structured (relational DB-style), unstructured (IR-style), and partly structured (NoSQL) data. Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …”
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134
Practical single node failure recovery using fractional repetition codes in data centers
Published 2016“…Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…In order to mitigate the charging effects of electric vehicles on the hybrid AC–DC microgrid operation, some remotely switches are considered in the system which make it possible for changing the topology and power flow way. In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …”
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137
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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Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
Published 2021“…Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”
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KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”