Search Results - (( based estimation path algorithm ) OR ( parameter classification using algorithm ))
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…The estimated CVDs path model can be implemented as a disease delay strategy in clinical settings. …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…Using this method, the need for the knowledge of the degree of nonlinearity in advance can be avoided. The proposed algorithm models the Wiener-Hammerstein linear and nonlinear components in the secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design.In previous works, SEF-NLFXLMS and THF-NLFXLMS algorithms for Hammerstein and Wiener structures were developed where the acoustic path is assumed to be a unit gain. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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Analysis of Dijkstra’s and A* algorithm to find the shortest path
Published 2015“…In this study, two algorithms will be focused on. This study compares the Dijkstra’s, and A* algorithm to estimate search time and distance of algorithms to find the shortest path. …”
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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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Delay-based load-balancing routing (DLBR) algorithm for wireless ad-hoc networks
Published 2015“…By combining physical layer capacity with MAC layer estimated congestion value, a new delay-based load-balancing routing (DLBR) algorithm is proposed in this paper. …”
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Delay-based load-balancing routing (DLBR) algorithm for wireless ad-hoc networks
Published 2015“…By combining physical layer capacity with MAC layer estimated congestion value, a new delay-based load-balancing routing (DLBR) algorithm is proposed in this paper. …”
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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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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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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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A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments
Published 2021“…This algorithm, also known as laser simulator logic, has the capability to estimate the inertia moment of the AFC-controller when the robot is moving in a pre-planned path with the presence of noisy measurements. …”
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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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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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An adaptive relay selection scheme for enhancing network stability in VANETs
Published 2020“…In this paper, we propose a new improvement to the mechanism of the Optimized Link State Routing Protocol(OLSR) protocol, named Cluster-based Adept Cooperative Algorithm (CACA), where each vehicle estimate a reliable low-overhead path using the cluster-based QoS algorithm. …”
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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
