Search Results - (( using function a algorithm ) OR ( parameter classification modeling algorithm ))
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…Fuzzy modeling is a process of generating parameters which are fuzzy rule and membership function. …”
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Undergraduates Project Papers -
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…They can be useful for taking a decision on choosing concrete values of traffic classification environments element parameters in a real network. …”
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Since, ANFIS use fuzzy logic, the model accuracy is highly dependent on selecting the appropriate type of membership function. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Improved back propagation neural network for the diagnosis of pathological voices
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali
Published 2017“…Additionally, it is demonstrated that a classification model can be created by staking the SOM model with a Linear Discrimination Analysis model, and the performance of this model is compared with other classification models. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…In this study, we propose a learning algorithm for the training of MLP models. …”
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Conference or Workshop Item -
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023Article -
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Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery
Published 2017“…The authors propose an UAV approach that utilises a digital surface model and incorporates a stereo matching algorithm based on UAV stereo images. …”
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Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah
Published 2017“…Hence, the success of CAWS system relies very much on whether the activation algorithm or model used is able to indicate a minimum safe distance precisely and timely. …”
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Handgrip strength evaluation using neuro fuzzy approach
Published 2010“…Handgrip assessment is a useful method to monitor patient rehabilitation. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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