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281
A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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282
Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…This study uses the above facility in developing algorithms for digitally determining the basic pulse parameters and tackling the problem of pulse pile-up in Gamma-ray spectroscopy. …”
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283
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”
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Advancing Data Center Networks: A Focus on Energy and Cost Efficiency
Published 2023“…These topologies must incorporate fault-tolerant and efficient routing algorithms. Consequently, the data center network topology must dynamically adapt to ever-changing application requirements. …”
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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. Here, the proposed DRF-DBRF security model's performance is validated and tested using five different and popular IoT benchmarking datasets. …”
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LaScaDa: A Novel Scalable Topology for Data Center Network
Published 2020“…LaScaDa forwards packets between nodes using a new hierarchical row-based routing algorithm. …”
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Heat rate curve approximation for power plants without data measuring devices
Published 2012“…The method is applied on a given power system, in which we calculate the electricity cost using the CAPSE (computer aided power economics) algorithm. …”
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290
UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices
Published 2019“…The global evolution of wireless technologies and intelligent sensing devices are transforming the realization of smart cities. Among the myriad of use cases, there is a need to support applications whereby low-resource Internet of Things (IoT) devices need to upload their sensor data to a remote control centre by target hard deadlines; otherwise, the data becomes outdated and loses its value, for example, in emergency or industrial control scenarios. …”
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291
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…Using three statistical measures Lyapunov exponents (LE), Correlation Dimension (CD), and approximate entropy (AE), we evaluated the performance of machine learning algorithms over different data lengths. …”
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XBeGene: Scalable XML Documents Generator by Example Based on Real Data
Published 2012“…XML datasets of various sizes and properties are needed to evaluate the correctness and efficiency of XML-based algorithms and applications. While several downloadable datasets can be found online, these are predefined by system experts and might not be suitable to evaluate every algorithm. …”
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A data envelopment analysis model for opinion leaders’ identification in social networks
Published 2024“…Social Network Analysis (SNA)-based OLs finding methods deal with a considerable amount of data due to using entire relationships between all of the users in a network, which makes the algorithms time-consuming. …”
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BioNetApp: An interactive visual data analysis platform for molecular expressions
Published 2019“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”
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Automatic keyword extraction from a real estate classifieds data set
Published 2011“…We begin with designing data cleansing algorithms to verify different attributes of the real estate classified. …”
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298
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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Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 2025“…Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”