Search Results - (( developing small selection algorithm ) OR ( java implementation path algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…This technique has the problem of selecting a significant number of test cases even for small changes made to a software. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Clonal selection algorithm for the cryptanalysis of a simple substitution cipher
Published 2006“…The development of Clonal Selection Algorithm (CSA) is inspired by elements from clonal selection theories. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection
Published 2011“…One of most used clustering 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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A model for gene selection and classification of gene expression data
Published 2007“…A model for gene selection and classification has been developed by using a filter approach, and an improved hybrid of the genetic algorithm and a support vector machine classifier. …”
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification
Published 2021“…For this purpose, the binary version of swarm algorithms facilitated with the S-shaped or sigmoid transfer function known as binary whale optimization algorithm (BWOA), binary particle swarm optimiza-tion algorithm (BPSO), and new binary manta-ray foraging opti-mization algorithm (BMRFO) are developed for feature selection. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses -
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Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem
Published 2018“…Material and methods: To test the proposed technique, selected approximation algorithms have been developed to small graph instances. …”
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Application of fuzzy clustering analysis to compound datasets for drug lead identification
Published 2012“…One of most used compound selection method is clusterbased 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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Proceeding -
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Numerical analysis
Published 2008“…In the numerical solution of differential equations, where the numerical approximation is developed in small time-steps, there are typically three challenges. …”
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions
Published 2025“…Many clustered routing algorithms have been developed to address various issues like energy efficiency, network lifetime, and hotspot problems. …”
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New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique
Published 2016“…There are 6 main designs that the algorithms proposed namely the Orthogonal-Diamond Search Algorithm with Small Diamond Search Pattern (ODS-SDSP), the Orthogonal-Diamond Search Algorithm with Large Diamond Search Pattern (ODS-LDSP), the Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (DOS-SDSP), the Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (DOS-LDSP), the Modified Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (MDOS-SDSP), and the Modified Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (MDOS-LDSP). …”
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Selecting informative genes from leukemia gene expression data using a hybrid approach for cancer classification
Published 2007“…We introduce an improved version of hybrid of genetic algorithm and support vector machine for genes selection and classification. …”
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Book Section -
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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat
Published 2021“…The benefit of this work indicated that the implementation of a feature selection technique plays an important role in machine learning algorithms to increase the performance of detection.…”
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Thesis
