Search Results - (( data optimization means algorithm ) OR ( data detection method algorithm ))
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1
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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2
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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3
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 -
4
Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Then, the feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. …”
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5
A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…Overall, the proposed methods achieve a 4.26% mean absolute error of chewing count estimation.…”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…Overall, the proposed methods achieve a 4.26% mean absolute error of chewing count estimation.…”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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9
Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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10
Hydraulic characterization of PVC-O pipes by means of transient tests
Published 2019“…The obtained results indicate that when the distance of the leakage increase, the accuracy of the detected data would be less accurate, and when the pressure of the pipeline decreases, the detected data would be less accurate also. …”
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Research Report -
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri
Published 2024“…Through the analysis of various customer data sets, such as people, products, promotion, place, the K-means algorithm can detect clusters that correspond to consistent client groups. …”
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13
Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…It is shown that the computational complexity of proposed FAST-QR detection algorithm is approximately 48 % lower than the conventional QR decomposition detection algorithm. …”
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Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Model 2 of CNN has maximum performance of validation in terms of accuracy, precision, sensitivity and specificity but the calibration model requires more optimization. The accuracy of the CNN model is comparable with the accuracy of the previous work that utilizing CNN for the imaging data to detect caries (diagnostic tool).…”
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15
Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel
Published 2016“…Results show that the defect detection algorithm able to detect defect only on the scratch area and able to read the Ga value at detected scratch line and transform it to surface roughness measurement at considerably good level of accuracy compared with manual method. …”
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16
Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO)
Published 2024“…However, the numerical results of The Relative Error (RE) and the Mean Error (ME) reveal that the observed and anticipated data are in line with the results. …”
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Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules
Published 2023“…The second algorithm uses K Nearest Neighbour using a ratio of training data and testing data of 95:05 resulting in an accuracy value of 62%. …”
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Assessment of landsat 7 scan line corrector-off data gap-filling methods for seagrass distribution mapping
Published 2015“…For optimal performance of the GNSPI algorithm, cloud and shadow in the primary and auxiliary images had to be removed by cloud removal methods prior to filling data gaps. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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