Search Results - (( data application testing algorithm ) OR ( variable interactive learning algorithm ))
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Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique
Published 2017“…Sensitivity testing of the BRT model was conducted to determine the best parameters and good explanatory variables. Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of two hidden layers with six and seven neurons in the first and second layers, respectively for xylitol stearate and xylitol palmitate and also seven and five neurons in the first and second layers for xylitol caprate, with hyperbolic tangent sigmoid transfer function. …”
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Revolutionizing video analytics: a review of action recognition using 3D
Published 2024“…It also addresses the practicalities of implementing action recognition algorithms in real-world situations, which include tools like deep learning frameworks, pre-trained models, open-source libraries, cloud services, GPU acceleration, and evaluation metrics. …”
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining
Published 2009“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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Book Chapter -
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
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Support vector machine in precision agriculture: a review
Published 2021“…The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which may be used for acquiring solutions towards better crop management. …”
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Fsm-Based Enhanced March C- Algorithm For Memory Built-In Self-Test
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…However the average classification accuracy of 84.74% on the unseen test data did not achieve the acceptable average success rate of 90% in this application. …”
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ANALYSIS AND INTERPRETATION OF PRESSURE TRANSIENT TEST DATA BY RECENT ROBUST DECONVOLUTION METHODS
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Final Year Project -
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia
Published 2024“…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”
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Fault detection with optimum March test algorithm
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Randomness Tests On Nine Data Categories Of RECTANGLE Using NIST Statistical Test Suite
Published 2024Article -
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia
Published 2025“…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”
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Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa
Published 2012“…The data included in the system is a tested and accurate data. …”
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Parallelization of noise reduction algorithm for seismic data on a beowulf cluster
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