Search Results - (( based internalization based algorithm ) OR ( sequence optimization method algorithm ))

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  1. 1

    Product assembly and disassembly sequence optimization based on genetic algorithm and design for assembly methodologies by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam

    Published 2009
    “…In this paper, an Artificial Intelligence (AI) technique, namely Genetic Algorithm (GA) is proposed to optimize product components assembly and disassembly sequences.The proposed methodology is developed and tested on an industrial product made of plastics with no integrated assembly and permanent joint parts.GA method is applied to determine the accuracy and optimum results based on 20 assembly and disassembly sequence solutions that was generated by the Design for Assembly methodology.The results indicated that GA based approach is able to obtain a near optimal solution for assembly and disassembly sequences.…”
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  2. 2

    Product assembly sequence optimization based on genetic algorithm by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam, Omar, Mazni, Syed-Abdullah, Sharifah Lailee

    Published 2010
    “…A single objective GA is used to obtain the optimal assembly sequence, exhibiting the minimum time taken. …”
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    Article
  3. 3

    An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm by Ibrahim, I., Ibrahim, Z., Ahmad, Hamzah, Jusof, M.F.M., Yusof, Z.M., Nawawi, S.W., Mubin, M.

    Published 2015
    “…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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    Article
  4. 4

    An Assembly Sequence Planning Approach with a Rule-based Multi-state Gravitational Search Algorithm by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Marizan, Mubin

    Published 2015
    “…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…This paper proposes a deep learning framework for human action recognition to overcome the drawbacks of the current state-of-the-art methods. To extract the appearance based and structural information, each frame of the action sequences is evaluated for spatial features. …”
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  9. 9

    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

    Published 2019
    “…In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K) , ASP with Clasp , CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). …”
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    Particle swarm optimization with partial search to solve traveling salesman problem by Akhand, M.A.H., Akter, Shahina, Rahman, S. Sazzadur, Rahman, M.M. Hafizur

    Published 2012
    “…Existing method introduced the idea of Swap Operator (SO) and Swap Sequence (SS) in PSO to handle TSP. …”
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    Proceeding Paper
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    Velocity tentative PSO: An optimal velocity implementation based particle swarm optimization to solve traveling salesman problem by M. A. H., Akhand, Shahina, Akter, M. A., Rashid

    Published 2015
    “…This paper introduces an effective Particle Swarm Optimization (PSO) based algorithm for solving Traveling Salesman Problem (TSP). …”
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    Article
  15. 15

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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  16. 16

    Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali *, Siti Maryam, Ahmad Kendong, Hajar, Fauzan Ahmad

    Published 2024
    “…Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. …”
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    Article
  17. 17

    Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

    Published 2018
    “…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Application of genetic algorithm method to optimize flow shop sequencing problem as the title of this project is the study about the method used in order to optimize flow shop sequencing problem. …”
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    Undergraduates Project Papers
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    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Raja Mohd Taufika, Raja Ismail

    Published 2019
    “…This paper addresses a data-driven neuroendocrine-PID tuning for the control of a two-input-two-output (TITO) coupled tank system with sto-chastic input time delay based on safe experimentation dynamics (SED). The SED algorithm is an optimization method used as data-driven tools to find the optimal control parameters by using the input-output (I/O) data measurement in an actual system. …”
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    Performance comparison of some addition chain methods based on integer family by Mohd Fadzil, Abdul Kadir, Mustafa, Mamat, Mohamad Afendee, Mohamed, Mohamad, R, Muhammed, A

    Published 2019
    “…There is no known algorithm which can calculate an optimal addition chain for a given number with any guarantees of reasonable timing or small memory usage. …”
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