Search Results - (( based constructive based algorithm ) OR ( user optimization based algorithm ))

Refine Results
  1. 1

    Ant colony optimization (ACO) algorithm for CNC route problem by Wan Nur Farhanah , Wan Zakaria

    Published 2012
    “…The GUT will be display the shortest path that should be taken by user and give user authority to manipulate the coordinate based on the requirement.…”
    Get full text
    Get full text
    Undergraduates Project Papers
  2. 2
  3. 3

    Web service applications and consumer environments based on ICT-driven optimization by Fan, Chaozhi, Law, Siong Hook, Ibrahim, Saifuzzaman, Ahmad, Mohd Naseem

    Published 2022
    “…Therefore, this paper proposes a service recommendation model based on the hybrid embedding of multiple networks and designs a multinetwork hybrid embedding recommendation algorithm. …”
    Get full text
    Get full text
    Article
  4. 4

    Innovation of marketing supply chain management model based on SICAS modeling by Mao, Rui, Liu, Youwei, Yang, Yida

    Published 2024
    “…A collaborative optimization model of the supply chain based on virtual inventory management is constructed to ensure the normal operation of the whole supply chain by deploying flexible inventory in the hands of customers, and the constructed model is solved by using an evolutionary algorithm based on indexes and an optimal solution sorting method based on regret theory. …”
    Get full text
    Get full text
    Article
  5. 5

    Agreement options for negotiation on material location decision of housing development by Utomo, C., Rahmawati, Y.

    Published 2020
    “…A support model enables negotiation process in group decision. Decision algorithms are based on the cooperative game theory to develop the agreement options and coalition formation. …”
    Get full text
    Get full text
    Article
  6. 6

    Power allocation with non-orthogonal multiple access for 5G heterogeneous network by Johari, Muhammad Amirul Aiman, Anwar Apandi, Nur Ilyana, Muhammad, Nor Aishah

    Published 2023
    “…The system models were derived to analyze the power performance based on the power allocation factor. An algorithm is constructed based on the deep learning coordinated multi-point to simulate the performance of the downlink 5G. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Detecting video spammers in YouTube social media by Yusof, Yuhanis, Sadoon, Omar Hadeb

    Published 2017
    “…Even though the detection of malicious users is based on various features such as content details, social activity, social network analyzing, or hybrid, the detection rate is still considered low (i.e. 46%).This study proposes a new set of features by constructing features based on the Edge Rank algorithm.Experiments were performed using nine classifiers of different learning; decision tree, function-based and Bayesian. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  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. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    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 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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    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
    “…All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Predicting next page access by Markov models and association rules on web log data by Chimphlee, S., Salim, N., B. Ngadiman, M. S., Chimphlee, W., Srinoy, S.

    Published 2006
    “…In this paper, we propose a method for constructing first-order and second-order Markov models of Web site based on past visitor behavior compare with association rules technique. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Multiple and solid data background scheme for testing static single cell faults on SRAM memories by Zakaria, Nor Azura

    Published 2013
    “…Therefore, the purpose of this thesis is to introduce a Data Background (DB) scheme to generate an optimal March Test Algorithm (MTA) for detecting faults of memory that are undetectable using existing algorithms. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Energy-efficient medium access control strategy for cooperative wireless networks by Sami, Mahmoud

    Published 2016
    “…In EAP-CMAC, the best transmission mode is selected among direct transmission, traditional cooperation and PNC-based transmission by considering the destination queue and source-destination link quality.Moreover, a joint relay selection and power allocation algorithm is proposed based on location information and the nodes residual energy that significantly improves the network lifetime and energy saving in wireless networks. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Robust multi-user detection based on hybrid grey wolf optimization by Ji, Yuanfa, Fan, Z ., Sun, X., Wang, S., Yan, S., Wu, S., Fu, Q., Kamarul Hawari, Ghazali

    Published 2020
    “…The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter