Showing 1 - 20 results of 84 for search '(((( elements ipca algorithm ) OR ( component system algorithm ))) OR ( neural coding algorithm ))', query time: 0.14s Refine Results
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    A pragmatic approach for testing robustness on real-time component based systems by Tarhini, Abbas

    Published 2005
    “…In this paper, we suggest a realistic methodology for testing robustness of real-time component-based systems (RTCBS). A RTCBS system is described as a collection of components where each component is specified by a nominal and a degraded specification, modeled as a timed input-output automaton (TIOA). …”
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    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

    Published 2024
    “…The proposed algorithm has been tested on three tank system pilot plant and Ain El Kebira Cement rotary kiln process. …”
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    A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

    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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    Thermodynamic Analysis and Optimization of Densely-Packed Receiver Assembly Components in High-Concentration CPVT Solar Collectors by Sharaf, Omar Z.

    Published 2016
    “…However, accurate design models and clear simulation algorithms on the component-level are critical for the proper system-level engineering and evaluation of CPVT collectors. …”
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    Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques by Kais Abdulmawjood (17947784)

    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. …”