Search Results - (( java application testing algorithm ) OR ( systematic implementation svm algorithm ))

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    Prediction of COVID-19 outbbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

    Published 2024
    “…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. …”
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    Thesis
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    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
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    Modeling and implementation of space vector modulation for three-phase direct torque control matrix converter by Ruzlaini, Ghoni

    Published 2013
    “…The duty cycles of the switches are modeled using SVM for 0.65 voltage transfer ratios. The mathematical models for the proposed systems are implemented by using Matlab/Simulink for different speed and load. …”
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    Thesis
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    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
    “…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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    Journal
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    Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

    Published 2014
    “…Finally, a novel hybrid Quantum-Inspired Evolutionary Programming - Least-Squares Support Vector Machine (QIEP-SVM) was presented. The results showed that the QIEP-SVM model had shown better prediction performance as compared to classical ANN, LS-SVM and QIEP-ANN.…”
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    Thesis
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    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2021
    “…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  7. 7

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2021
    “…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  8. 8

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2022
    “…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  9. 9

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2022
    “…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  10. 10

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2022
    “…Findings: A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
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    Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

    Published 2014
    “…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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    Undergraduates Project Papers
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    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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    Thesis
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    Encrypted mobile messaging application using AES block cipher cryptography algorithm / Nur Rasyiqah Zulkifli by Zulkifli, Nur Rasyiqah

    Published 2019
    “…The programming language that is used to write the program is Java Language that will run on android phones. As the result, this project was tested on the functionality of the mobile messaging application. …”
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    Student Project
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