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algorithm module » algorithm novel (Expand Search)
algorithm pca » algorithm fa (Expand Search), algorithm goa (Expand Search), algorithm a (Expand Search)
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An incremental approach for test scheduling and synthesis using genetic algorithms
Published 2017“…This method maximizes concurrent testing of modules while performing the allocation of functional units, test registers, and multiplexers. …”
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…The method maximizes concurrent testing of modules while performing the allocation of functional units, test registers, and interconnects. …”
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link
Published 2023“…The load types are time-modulated, magnitude-modulated, time-and-magnitude-modulated, and fixed. …”
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Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm
Published 2018“…<p dir="ltr">This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. …”
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Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems
Published 2009Get full text
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Software defect prediction. (c2019)
Published 2019“…This is normally measured at the level of a module. A module is a class in the object-oriented design or a function in the procedural design. …”
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Exploring the Dynamic Interplay of Deleterious Variants on the RAF1–RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics
Published 2024“…Hence, the current study focuses on the screening of clinically reported substitutions in the <i>RAF1</i> and <i>RAP1A</i> genes using predictive algorithms integrated with all‐atoms simulation, essential dynamics, and binding free energy methods. …”
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Timing influenced general-cell genetic floorplanner
Published 2020“…In the first phase we use the genetic algorithm and restrict the modules to be rigid and the floorplan to have slicing structure. …”
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features
Published 2024“…Next, principal component analysis (PCA) is used to select the best subset of attributes. …”
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Autonomous Robot Navigation Based On Recurrent Neural Networks
Published 2012Get full text
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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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Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
Published 2021Get full text
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A simplified sliding‐mode control method for multi‐level transformerless DVR
Published 2022“…Second, an effective method based on charging/discharging conditions of DC capacitors is proposed for balancing capacitor voltages using relevant switching state rather than combining DC voltage error with the inductor current error through a suitable weighting factor in forming the cost function. Therefore, the weighting factor necessity in the control algorithm is eliminated. …”
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IoT-Based Sustainable Parking Lot
Published 2023“…Experimental results showed that the system was able to perform the functionality with high accuracy. The coefficient of determination (R²) achieved of the car congestion prediction module was 0.97. …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins
Published 2025“…Unlike standard machine learning approaches such as PCA, LDA, SVM, RF, GBM etc, DeepRaman functions independently, requiring no human interaction, and can be used to much smaller datasets than traditional CNNs. …”
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