Search Results - (( software identification based algorithm ) OR ( data optimization method algorithm ))
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1
Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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2
Three phase fault algorithm in distribution system by using database approach and impedance based method
Published 2012“…A three phase fault location algorithm using database and impedance based method is utilized in distribution system to locate fault which may occur in any possible fault sections and to optimize the switching operations to reduce the outage time affected by fault. …”
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3
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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4
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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5
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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6
Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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7
Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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8
Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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Proceeding Paper -
9
Assessment of ANN-based auto-reclosing scheme developed on single machine-infinite bus model with IEEE 14-bus system model data
Published 2009“…Consequently, improper reclosing of the line onto a fault is avoided. The fault identification prior to reclosing is based on optimized artificial neural network associated with three different training algorithms. …”
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10
Fuzzy modelling using firefly algorithm for phishing detection
Published 2019“…To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods provides the Firefly Algorithm (FA). …”
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11
Rule Prioritisation Heuristic in Shift Design of Airline Ground Crew
Published 2024“…Empirical tests reveal the proposed heuristic method's superiority over manual practices and genetic algorithms. …”
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12
Modeling the powder compaction process using the finite element method and inverse optimization
Published 2011“…Minimization of the objective function with respect to the material parameters was performed using an in-house optimization software shell built on a modified Levenberg–Marquardt method. …”
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13
Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…The parameters may vary as environmental conditions change. It requires big data and consumes a long time. This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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14
Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm
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15
Register Transfer Level Implementation Of Pooling - Based Feature Extraction For Finger Vein Identification
Published 2017“…The proposed algorithm extracted the local feature information of the finger vein pattern (patches), and used these patches to improve the robustness of the identification. …”
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16
Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali
Published 2022“…In this case, the algorithm of the DIS operator is embedded with the Marker-based Watershed segmentation as the assistance of Marker-based Watershed Segmentation is effective in extracting the individual significant edges features produced by DIS operator. …”
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17
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…Software quality is an important research area and has gain considerable attention from software engineering community in identification of priority quality attributes in software development process. …”
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18
On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee
Published 2021“…The experimental results demonstrate that the proposed framework is practical and effective, with < 2.3% of relative error at the Nyquist frequency as compared to the well-established edge method. In continuation of the first framework, the proposed MTF measurement algorithms are evaluated experimentally as a blur kernel estimation method for spatially varying and invariant blur removal. …”
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19
Texture-based feature using multi-blocks gray level co-occurrence matrix for ethnicity identification
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