Search Results - (( java implementation path algorithm ) OR ( knowledge states pattern algorithm ))

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  1. 1

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    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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    Thesis
  2. 2

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    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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  3. 3

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    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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    Article
  4. 4

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    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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  5. 5

    An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

    Published 2004
    “…Data mining is a challenging matter in research field for the last few years.Researchers are using different techniques in data mining.This paper discussed the initial state of Design and Development Intelligent Knowledge Discovery System for Stock Exchange (SE) Databases. …”
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    Conference or Workshop Item
  6. 6

    Study on the influence of knowledge-driven technology on predicting consumer repurchase behaviour by Chen, Yajing, Leong, Yee Choy, Yiing, Lee Shin, Xiao, Yunxia

    Published 2023
    “…In this prospect, many MNCs and other enterprises harness contemporary computing technologies like Big Data Analytics, Deep Learning and Predictive Analytics to explore the latent knowledge in purchase patterns and customer behaviour. …”
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  7. 7

    Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

    Published 2004
    “…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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    Conference or Workshop Item
  8. 8
  9. 9

    Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Othman, Mohammad Ridzal, Osman, Harussaleh

    Published 2011
    “…Using the area under the ROC curve measurements, the CD-decision algorithm has been verified to be able to predict as well as discriminate future unknown-trip-state relay events in unsupervised learning. …”
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    Article
  10. 10

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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  11. 11

    Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking by Ong, Chor Keat

    Published 2017
    “…Visual tracking has become one of the most important components in computer vision as the knowledge in this field can be applied into a wide range of applications in computer vision such as medical imaging, pattern recognition, video surveillance, industrial robot, computer-human interaction, etc. …”
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    Monograph
  12. 12

    Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

    Published 2019
    “…The actual KAP on dengue that was inadequate among the respondents were verified and revealed with PLS-PA. The knowledge that was inadequate among the respondents were knowledge on primary and secondary transmission of dengue fever, knowledge on possible breeding sites of dengue vectors and knowledge on the severity of dengue fever and vectors. …”
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  13. 13
  14. 14

    A comparative study between rough and decision tree classifiers by Mohamad Mohsin, Mohamad Farhan

    Published 2008
    “…Theoretically, a good set of knowledge should provide good accuracy when dealing with new cases.Besides accuracy, a good rule set must also has a minimum number of rules and each rule should be short as possible.It is often that a rule set contains smaller quantity of rules but they usually have more conditions.An ideal model should be able to produces fewer, shorter rule and classify new data with good accuracy.Consequently, the quality and compact knowledge will contribute manager with a good decision model.Because of that, the search for appropriate data mining approach which can provide quality knowledge is important.Rough classifier (RC) and decision tree classifier (DTC) are categorized as RBC.The purpose of this study is to investigate the capability of RC and DTC in generating quality knowledge which leads to the good accuracy.To achieve that, both classifiers are compared based on four measurements that are accuracy of the classification, the number of rule, the length of rule, and the coverage of rule.Five dataset from UCI Machine Learning namely United States Congressional Voting Records, Credit Approval, Wisconsin Diagnostic Breast Cancer, Pima Indians Diabetes Database, and Vehicle Silhouettes are chosen as data experiment.All datasets were mined using RC toolkit namely ROSETTA while C4.5 algorithm in WEKA application was chosen as DTC rule generator.The experimental results indicated that both classifiers produced good classification result and had generated quality rule in different types of model – higher accuracy, fewer rule, shorter rule, and higher coverage.In term of accuracy, RC obtained higher accuracy in average while DTC significantly generated lower number of rule than RC.In term of rule length, RC produced compact and shorter rule than DTC and the length is not significantly different.Meanwhile, RC has better coverage than DTC.Final conclusion can be decided as follows “If the user interested at a variety of rule pattern with a good accuracy and the number of rule is not important, RC is the best solution whereas if the user looks for fewer nr, DTC might be the best choice”…”
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    Monograph
  15. 15

    The Rise of Blockchain Internet of Things (BIoT): Secured, Device-to-Device Architecture and Simulation Scenarios by Arun Rana, Sharad Sharma, Kashif Nisar, Ag. Asri Ag. Ibrahim, Sachin Dhawan, Bhawani Chowdhry, Samreen Hussain, Nitin Goyal

    Published 2022
    “…As a result, to deliver acceptable services, a new solution is necessary to secure data accountability, increase data privacy and accessibility, and extract hidden patterns and usable knowledge. Moving the Internet of Things to a distributed ledger system might be the most effective way to solve these issues. …”
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    Article
  16. 16

    Query proof structure caching for incremental evaluation of tabled prolog programs / Taher Muhammad Ali by Taher Muhammad, Ali

    Published 2013
    “…These mechanisms are pattern-matching, treebased data structuring and backtracking. …”
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