Search Results - (( parameter evaluation method algorithm ) OR ( using interactive learning algorithm ))
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
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Application of Decision Tree Algorithm for Predicting Monthly Pan Evaporation Rate
Published 2023Conference Paper -
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…The synthetic reaction was optimized by Taguchi method based on orthogonal array to evaluate the effect of each parameters and interactive effects of reaction parameters including temperature, time, amount of enzyme, amount of molecular sieve, amount of solvent, and molar ratio of substrates (xylitol: fatty acid). …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems
Published 2025“…The channel parameters such as received power, time of arrival, and angle of arrival are used as fingerprint features that act as predictors in both learning sessions. …”
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Comparative analysis of PCA and ANOVA for assessing the subset feature selection of the geomagnetic Disturbance Storm Time / Ain Dzarah Nafisah Mazlan … [et al.]
Published 2020“…The main aims for this works are to reduce a large set of input parameters from the Dst index and to compare the subset feature using the proposed methods for acquiring the reduced features. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…Existing works and solutions focused on separate models for recognizing the residents, activities and interactions. On top of that, data association and algorithm modification inherit drawbacks on recognizing the residents and interactions of multi-resident complex activities. …”
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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…The gray relational grade (GRG) performance metric and the Friedman test were used to evaluate the algorithm’s performance. The Taguchi-GRA method that produced the new values for the algorithm’s parameters was shown to be able to provide a better multi-objective generator maintenance scheduling (GMS) solution. …”
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Evaluation of lightning current parameters using measured lightning induced voltage on distribution power lines
Published 2019“…In this paper, an algorithm had been proposed to evaluate the lightning current parameters using measured voltage from overhead distribution lines based on lightning location obtained from lightning location system. …”
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Conference or Workshop Item -
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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Designing algorithm visualization on mobile platform: The proposed guidelines
Published 2017“…In fact, mobile learning has been proved to enhance engagement in learning circumstances, and thus effect student’s performance.In addition, the researchers highly recommend including UI design and Interactivity in designing effective AV system.However, the discussions of these two aspects in previous AV design guidelines are not comprehensive.The UI design in this paper describes the arrangement of AV features in mobile environment, whereas interactivity is about the active learning strategy features based on learning experiences (how to engage learners). …”
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Comparative study of machine learning algorithms in data classification
Published 2025“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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Interactive framework for dynamic modelling and active vibration control of flexible structures
Published 2008“…The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…The proposed method considers on all electromagnetic fields components and can evaluate full shape of current, velocity and constant parameters of current models in contrast with previous studies. …”
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Fast and efficient sequential learning algorithms using direct-link RBF networks
Published 2003“…The dynamic DRBF network is trained using the recently proposed decomposed/parallel recursive Levenberg Marquardt (PRLM) algorithm by neglecting the interneuron weight interactions. …”
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