Search Results - (( 3d visualisation ((a algorithm) OR (new algorithm)) ) OR ( case selection based algorithm ))*
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Effectiveness of silhouette rendering algorithms in terrain visualisation
Published 2002“…This approach has been implemented in a 3D modelling system to create a new method of displaying and viewing terrain data in an artistic style. …”
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Axis manipulation to solve Inverse Kinematics of Hyper-Redundant Robot in 3D Space
Published 2022“…In this study, an axis manipulation using a geometrical approach is used. Initially, a general algorithm for a 2-m-link hyper-redundant robot in 3D is generated. …”
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3D terrain visualisation for GIS: A comparison of different techniques
Published 2011“…Geographic Information System (GIS) applications are now moving towards 3D as it has a better representation of the real world.Most GIS applications now can be visualised not only in 2D but also in 3D.Currently most of the applications are capable of operating in an online environment such as Google Earth, Microsoft Virtual Earth and World Wind.Recently, many people use these online applications for their daily work and also for decision making.Terrain visualisation is an important aspect for these three applications, in visualizing the world in 3D.The quality of terrain visualisation depends on the techniques used by the developer.The research for generating good quality terrain visualisation for depicting the real world is ongoing and faces big challenges. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm
Published 2007“…Among these selected test cases, the algorithm identifies the redundant test cases based on definition occurrence, if they cover a similar combination of branch coverage except in one branch and also if the test cases cover a similar definition occurrence . …”
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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…The goal is to compare different replacement strategies of GA and select the best strategy that will make prioritization to order selected test cases based on their fitness. …”
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Regression test case selection & prioritization using dependence graph and genetic algorithm
Published 2014“…The approach is based on optimization of selected test case from dependency analysis of the source codes. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…The approach is based on optimization of selected test case from test suite T. …”
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…This paper propose an optimized regression test case selection and prioritization for object-oriented software based on dependence graph model analysis of the source code and optimized the selected test case using Genetic Algorithm. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…A new case is retained in the case base for future retrievals. …”
Conference paper -
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An adaptive opposition-based learning selection: The case for jaya algorithm
Published 2021“…The results also show that OBL-JA performs better than standard Jaya Algorithm in most of the tested cases due to its ability to adapt its behaviour based on the current performance feedback of the search process.…”
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A fuzzy case-based reasoning model for software requirements specifications quality assessment
Published 2023“…Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. …”
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A prototype for driving school instructor timetabling using case-based heuristics selection algorithm / CT Munnirah Niesha Mohd Shafee
Published 2010“…This problem can be solved using Case-Based Heuristics Selection approaches. Then the project continues to find algorithm to be applied to generate a clash-free timetable. …”
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Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
Published 2016“…In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. …”
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Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz
Published 2016“…In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…In order to identify the strength and weakness of these algorithms for MC/DC compliant test cases, this research proposes an experimental study involving four neighborhoods based meta-heuristic algorithms. …”
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An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players
Published 2021“…A new combined decision model which integrates Analytical Network Process and Case-based Reasoning was developed. The algorithm converts the model to coding, structures the process of entering data, automates the calculations and presents the results in a well-organized and suitable interfaces for the team managerial review purposes. …”
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Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria
Published 2021“…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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