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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…Artificial Neural Networks (ANNs) are one of the most popular methods for classification in condition diagnosis of bearing systems.Regarding to ANNs performance, ANNs parameters have important role especially connectivity weights.In several running of learning processes with the same structure of ANNs, we can obtain different accuracy significantly since initial weights are selected randomly. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…One of most used compound selection method is cluster-based compound selection, which involves subdividing a set of compounds into clusters and choosing one compound or a small number of compounds from each cluster. …”
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Monograph -
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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…This research proposed an algorithm for improving the current working performance of Back-propagation algorithm by adaptively changing the momentum value and at the same time keeping the ‘gain’ parameter fixed for all nodes in the neural network. …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia
Published 2023“…However, standalone models, such as Artificial Neural Network (ANN), typically underperform during local convergence and resulted in slow-speed convergence. Thus, Bat Algorithm (BA) was used to enhance the efficiency of ANN in forecasting upstream river SF, as BA is capable of switching from the “explore to exploit” function which could increase the rate of convergence at the initial stage and deliver a quick result for a majority of a classification problem. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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Spectral and prosodic feature extractions for classical Arabic accents recognition among Malay speakers / Noor Jamaliah Ibrahim
Published 2021“…Therefore, it can be concluded that, integrating the prosodic and spectral features of MFCC, and incorporated with GMM-UBM classification in ASR system, outperforms other algorithms tested in this research. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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Conference or Workshop Item -
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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Undergraduates Project Papers -
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…IPJAYA in this study was used to update the C and gamma parameters of the support vector machine (SVM). …”
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Automatic selection of initial points for exploratory vessel tracing in fluoroscopic images
Published 2011“…This paper presents a new method for efficient selection of initial points for exploratory tracing algorithms. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Undergraduate Final Project Report
