Search Results - (( software evaluation means algorithm ) OR ( java implication based algorithm ))
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Software effort estimation using machine learning technique
Published 2023“…The three commonly used performance evaluation measures, mean absolute error (MAE), mean squared error (MSE), and R square error, represent the base for these. …”
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A balanced partitioning mechanism for multicontroller placement in software-defined wide area networks
Published 2022“…The network simulator OMNeT++ was configured to simulate the performance of BPM over the OS3E topology, with two scenarios including five and six domains. The K-means and CNPA algorithms, in particular, were used to evaluate the performance of BPM. …”
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Thesis -
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A Mobile Application For Stock Price Prediction
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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…These software applications have many sets of input values, parameters, software/hardware environments and system conditions, which need to be tested to ensure software reliability and quality. …”
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Algorithmic approaches in model selection of the air passengers flows data
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Analysis of Microscopic Blood Samples for Detecting Malaria
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Undergraduates Project Papers -
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Development of an imputation technique - INI for software metric database with incomplete data
Published 2007“…Its performance was evaluated and compared with two existing imputation techniques, Expectation Maximization (EM) and Mean Imputation (MI). …”
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A framework for automated quality assessment of software requirement specification based on part-of-speech tagging, multi-agent k-means clustering and case-based reasoning
Published 2022“…This process is performed through the Multi-Agent K-means (MA-K-means) model for handling the automatic evaluation of the AQA-SRS framework. …”
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System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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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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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification
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Breast Ultrasound Automated ROI Segmentation with Region Growing
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