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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
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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3
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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4
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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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
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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Schelkunoff array synthesis methods using adaptive-iterative algorithm
Published 2003“…Basically, this algorithm is a combination of iterative algorithm with adaptive algorithm. …”
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9
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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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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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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12
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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13
Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation
Published 2011“…Unlike a conventional PSOIACO algorithm, this hybrid algorithm shows improvement of the classification accuracy in its generated rough reducts to solve NP-Hard problem. …”
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14
Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…There are many methods to perform adaptive beamforming and one of the method is to use metaheuristic algorithm, to estimate the weights for individual elements in an array. …”
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15
A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
Published 2019“…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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Proceeding Paper -
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Detection of Counterfeit Telecommunication Products using Luhn Checksum Algorithm and an Adapted IMEI Authentication Method
Published 2020“…The first authentication method is the Luhn checksum algorithm, otherwise called Luhn formula or mod 10 algorithm. …”
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Simultaneous Adaptation Of Multiple Genetic Algorithm Parameters Using Fuzzy Logic Controllers
Published 2010“…This study aims at designing an online adaptive method to control multiple parameters of the Genetic Algorithm. …”
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19
Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…Classical methods like artificial potential field, grid search, and visual method have been easily overtaken by artificial intelligence due to its adaptability and ability to learn from the past mistakes or experience. …”
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20
Position control of robot manipulator: Design a novel SISO adaptive sliding mode fuzzy PD fuzzy sliding mode control.
Published 2011“…This algorithm will be analyzed and evaluated on robotic manipulators and design adaption laws of adaptive algorithms after that writing Lyapunov function candidates and prove the asymptotic convergence of the closed-loop system using Lyapunov stability theorem mathematically. …”
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