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injection algorithm » detection algorithm (Expand Search), auction algorithm (Expand Search)
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msa algorithm » jaya algorithm (Expand Search), rd algorithm (Expand Search)
injection algorithm » detection algorithm (Expand Search), auction algorithm (Expand Search)
encoding algorithm » cosine algorithm (Expand Search)
msa algorithm » jaya algorithm (Expand Search), rd algorithm (Expand Search)
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021Subjects: “…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…”
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The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
Published 2023“…We focus on the combined influence of data encoding, qubit entanglement, and ansatz expressibility in hybrid quantum neural networks (HQNNs) for multi-class classification tasks. …”
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Improving the Resilience of Smart Distribution Networks against Cyber Attacks
Published 2022Get full text
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Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security
Published 2024“…The aim is to demonstrate the robustness of the proposed algorithms in effectively identifying telnet, password, distributed denial of service (DDoS), injection, and backdoor vulnerabilities in IoT ecosystems. …”
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A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
Published 2022“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …”
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”
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Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks
Published 2023“…However, the traffic of digital information and communication is potentially vulnerable to data-injection and cyber attacks. To address this issue, a median regression function (MRF)-based state estimation is presented in this paper. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
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An Alternating Projection Framework for Elementwise Masked Nonlinear Matrix Decomposition
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Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach
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Competitive learning/reflected residual vector quantization for coding angiogram images
Published 2003“…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …”
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Design and analysis of entropy-constrained reflected residual vector quantization
Published 2002“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. …”
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Modelling of pollutant transport in compound open channels
Published 1998“…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …”
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Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier
Published 2021“…Modern ML models are used for prediction, prioritization, and decision making. Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”
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PERF solutions for distributed query optimization. (c1999)
Published 1999Get full text
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masterThesis