Search Results - (( simulation identification using algorithm ) OR ( evolution classification using algorithm ))
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1
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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2
Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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3
Identification algorithms of flexible structure using neural networks
Published 2006“…The finite duration step input is applied to simulation algorithm of the plate. Finally a comparative performance of the approaches used is presented and discussed.…”
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4
Iterative closed-loop identification of MIMO systems using ARX-based Leaky Least Mean Square Algorithm
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5
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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6
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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7
A Robust Firearm Identification Algorithm of Forensic Ballistics Specimens
Published 2017“…Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. …”
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8
Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS_Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS_Ch may offer a useful way for reliable enhancement of the detection of different emotional states of the brain regions.…”
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9
A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…The simulation model was developed using Active Server Page, JavaScript and SQL 7.0 as database. …”
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10
Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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11
Intersection Features For Android Botnet Classification
Published 2019“…The Chi Square was used to select the most significant permissions, then the classification algorithms like Naïve Bayes and Decision Tree were used to classify the Android apps as botnet or benign apps. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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13
Date store management in sliding window based on-line identification algorithms
Published 2001“…Sliding window identification algorithms use information from a store of data to optimise on-line learning. …”
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14
Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter
Published 2018“…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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Identification of hammerstain model using stochastic perturbation simultaneous approximation
Published 2016“…Furthermore, the Identification is done using MATLAB Simulink to simulate the Hammerstein Model. …”
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16
EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization
Published 2019“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali
Published 2022“…The system algorithm is verified and validates on two sloped bumps surface topographies that have been simulated using MATLAB software and measured using the Alicona Infinite Focus Measurement (IFM) device, respectively. …”
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18
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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Identification algorithms of flexible structure using neural networks
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. The best combinations were selected to train individual ARTMAPs as voting members, and the final class predictions were determined using probabilistic ensemble voting strategy. …”
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