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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. Initially, the features are grouped randomly to increase the probability of making them participating in the generation of different groups, and sorted based on their accuracy scores. …”
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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems
Published 2022“…This is addressed such that the genetic algorithm (GA) technique is used for selecting the best features and the artificial neural network (ANN) classifier is applied for fault diagnosis. …”
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Belief selection in point-based planning algorithms for POMDPs
Published 2017“…Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. …”
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Multi-marker-LD based genetic algorithm for tag SNP selection
Published 2014“…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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An enhanced quorum selection algorithm
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An Improved Quorum Selection Algorithm
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…Therefore, this thesis proposed a Novel Stacking Classification and Prediction (NSCP) algorithm based on AAL for the older people with Multi-strategy Combination based Feature Selection (MCFS) and Novel Clustering Aggregation (NCA) algorithms. …”
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Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems
Published 2023“…Therefore, an enhanced particle swarm optimization (PSO), data reduction, and interval-valued representation are proposed. First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …”
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Minimum traffic inter-BS SHO boundary selection algorithm for CDMA-based wireless networks
Published 2004“…An algorithm is presented to select an inter-base station soft handoff (inter-BS SHO) boundary for code division multiple access (CDMA)-based wireless networks. …”
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Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm
Published 2020“…Among the pre-programmed PWM techniques, Selective Harmonic Elimination (SHE) has been the prevailing solution, but recently, Selective Harmonic Mitigation (SHM) stands as a superior alternative to provide further control of the harmonic spectrum with similar losses. …”
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Empirical comparison of regression test selection algorithms
Published 2001“…In this paper, we empirically compare five representative regression test selection algorithms, which include: Simulated Annealing, Reduction, Slicing, Dataflow, and Firewall algorithms. …”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…Then, to improve even more the performances of the developed interval-valued SVM, multiscale data representation will be used to develop multiscale extensions of interval-valued SVM. Next, as a feature selection tool, an improved extension of Artificial Butterfly Optimization (ABO) algorithm is used in order to extract the significant features from data and improve the diagnosis results of multiscale interval SVM. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. …”