Search Results - (( java location based algorithm ) OR ( parameter welding learning algorithm ))

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  1. 1

    A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Alam, Mohammad Nur‑E, Soudagar, Manzoore Elahi Mohammad

    Published 2024
    “…This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). …”
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  2. 2

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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  3. 3

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Muhamad Aiman Raziq, Muhamad Aiman Raziq, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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  4. 4

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, MuhamadAiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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  5. 5

    Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, H. P. Manurung, Yupiter, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon6 & Vladimir S. Kachinskyi, John R. C. Dizon6 & Vladimir S. Kachinskyi

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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  6. 6

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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  7. 7

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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    Article
  8. 8

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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    Article
  9. 9

    A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Nur‑E‑Alam, Mohammad, Soudagar, Manzoore Elahi Mohammad

    Published 2024
    “…This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). …”
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    Article
  10. 10

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, MuhamadAiman Raziq, MuhamadAiman Raziq, ChengYee Low, ChengYee Low, Muhammad Saufy Rohmad, Muhammad Saufy Rohmad, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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    Article
  11. 11

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, MuhamadAiman Raziq, MuhamadAiman Raziq, ChengYee Low, ChengYee Low, Muhammad Saufy Rohmad, Muhammad Saufy Rohmad, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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  12. 12
  13. 13

    Group formation using genetic algorithm by Che Ani, Zhamri, Husin, Mohd Zabidin, Yasin, Azman

    Published 2009
    “…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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    Monograph
  14. 14

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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    Thesis
  15. 15
  16. 16

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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    Conference or Workshop Item
  17. 17

    Campus safe: Safeguarding GPS-based Physical Identity and Access Management (PIAM) system with a lightweight Geo-Encryption by Yeo Zi Zian

    Published 2022
    “…Subsequently, this project embedded with a lightweight Geo-Encryption algorithm to preserve the privacy of real-time GPS location. …”
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    Academic Exercise
  18. 18

    Friendship Degree and Tenth Man Strategy: A new method for differentiating between erroneous readings and true events in wireless sensor networks by Adday, Ghaihab Hassan, Subramaniam, Shamala K., Zukarnain, Zuriati Ahmad, Samian, Normalia

    Published 2023
    “…The second stage will validate the voting process through a novel perspective based on the TMS. TMS will check the voters’ replies based on the event’s location. …”
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  19. 19

    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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    Thesis
  20. 20

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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    Thesis