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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“…<p dir="ltr">Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. …”
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Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions
Published 2017“…For this purpose, computer programs based on updated pattern recognition algorithms were developed for joint-detection and classification of rock types to offer an estimated strength. …”
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Using machine learning for disease detection. (c2013)
Published 2016“…Classification has three main components: the classification algorithm, the pre-classified data (training data) and the un-classified data (testing data). …”
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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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Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques
Published 2025“…In the first stage, the WPT is used to split the PV voltage and string currents into specific sub-band frequencies, and then EMD is used to decompose the selected frequency bands into a number of intrinsic mode functions (IMFs) and a residual. The generated IMF components are then fed into the Random Forest (RF) algorithm designed for shading detection and classification. …”
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Semantics-based approach for detecting flaws, conflicts and redundancies in XACML policies
Published 2015“…All the approach components and algorithms realizing the proposed analysis semantics have been implemented in one development framework. …”
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A decoding algorithm for I-Q space-time coded systems in fadingenvironments
Published 2000“…Therefore, a simplified decoding algorithm is proposed. It is based on symbol-by-symbol detection of the Q/I components in the I/Q decoders. …”
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter
Published 2019“…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024“…In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. …”
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Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice
Published 2020“…Smart health systems can be an easy and fast support to voice pathology detection. The identification of an algorithm that discriminates between pathological and healthy voices with more accuracy is needed to obtain a smart and precise mobile health system. …”
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A novel hybrid methodology for fault diagnosis of wind energy conversion systems
Published 2023“…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”