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Data reductions and combinatorial bounds for improved approximation algorithms
Published 2016“…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …”
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Distributed dimension reduction algorithms for widely dispersed data
Published 2002“…It runs in linear time and requires very little data transmission. A series of experiments is conducted to gauge how the algorithm’s emphasis on minimal data transmission affects solution quality. …”
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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…Gamma pulses from a 3" Na(TI) scintillation detector were captured as single and double pulses for the purpose of testing the peak detection algorithms. The pulse classification technique was tested successfully on a TMS320C6000 high performance floating-point processor yielding a reduction of the execution time to 2 msec…”
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VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems
Published 2019“…In this paper, we introduce VHDRA, a Vertical and Horizontal Data Reduction Approach, to improve the classification accuracy and speed of the NNGE algorithm and reduce the computational resource consumption. …”
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Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. …”
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…The proposed approach deals with system uncertainties (current/voltage variability, noise, measurement errors, ⋯) by using an interval-valued data representation, and with large-scale systems by using a dataset size-reduction framework. …”
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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…The proposed algorithm has successfully maintained homogeneity to the original data set, reduced the execution time and occupied storage space, and led to decent monitoring performance.…”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
Published 2020“…A special consideration was given to data pre-processing and dimensionality reduction such Chi Squared (CS) and Recursive Feature Elimination (RFE) to improve progressively the proposed models performance. …”
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A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
Published 2025“…Given that Android applications are frequent targets for malware, ensuring the integrity of FL-based malware detection systems is critical. We introduce an attack framework that integrates Genetic Algorithms (GA) with two prominent adversarial techniques, namely, the Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD), specifically designed for FL environments. …”
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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Use of Data Mining Techniques to Detect Fraud in Procurement Sector
Published 2022“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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Evaluation of C-arm CT metal artifact reduction algorithm during intra-aneurysmal coil embolization
Published 2016“…This analysis was carried out to assess the improvements in both brain parenchyma and device visibility with MAR algorithm. Further, ground truth reference images from phantom experiments and clinical data were used for accurate assessment. …”
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems
Published 2023“…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …”
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Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations
Published 1992“…Three optimization methods derived from natural sciences are considered for allocating data to multicomputer nodes. These are simulated annealing, genetic algorithms and neural networks. …”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…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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