Search Results - (( variable training does algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…Multi-objective Genetic Algorithms (MOGA) are an extension of Genetic Algorithms (GA) that does not require multiple objectives to be aggregated to one value. …”
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Proceeding Paper -
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…As for the implementation of MPCA in feature extraction for BOD and COD, there were only 4 inputs required to explain at least 99.999% variability for both analyses. Altogether, for BOD, the BR algorithm with 60% training and 12 hidden nodes gives R=0.7825 whereas for COD, the BR algorithm with 70% training and 10 hidden nodes gives R=0.6716. …”
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Monograph -
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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Thesis -
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A novel computer-aided multivariate water quality index
Published 2015“…Results indicate that the algorithm is robust and reliable. Based on six parameters, the overall ratings derived are inversely correlated to DOE-WQI. …”
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Article -
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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Monograph -
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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Thesis -
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Thesis -
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Also a new algorithm for finding the initial point is proposed. …”
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Thesis -
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Model Prediction Of Pm2.5 And Pm10 Using Machine Learning Approach
Published 2021“…It was found that taking into account the removal of the irrelevant variables does not increase precision significantly nor does it reduce the performance tremendously. …”
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Monograph -
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Predicting Diseases Using Multi-BackPropagation
Published 2002“…Multi-network approach does not require any changes in neural network learning algorithm. …”
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Thesis -
12
Classification of water quality using artificial neural network
Published 2020“…Concentrations of these six parameters were used in the mathematical equation of the DOE-WQI technique and as input variables in the ANN database system. …”
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Thesis -
13
Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate
Published 2025“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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Article -
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A robust prioritization framework of data quality dimensions to improve ML-driven healthcare systems using AHP and sensitivity analysis
Published 2025“…In contrast to performance evaluation studies involving machine learning algorithms or classifiers, this research does not encompass the training or comparison of predictive models. …”
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Development and characterization of parenteral nano-delivery system loaded with azithromycin
Published 2016“…In order to achieve the optimum topologies, ANN was trained by Incremental Back-Propagation (IBP), Batch Back-Propagation (BBP), Quick Propagation (QP), and Levenberg- Marquardt (LM) algorithms for testing data set. …”
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Thesis -
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