Search Results - (( using function based algorithm ) OR ( sequence optimization approach algorithm ))

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  1. 1
    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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  2. 2
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
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  3. 3
    Improved opposition-based particle swarm optimization algorithm for global optimization

    Improved opposition-based particle swarm optimization algorithm for global optimization by Nafees Ul Hassan, Waqas Haider Bangyal, M. Sadiq Ali Khan, Kashif Nisar, Ag. Asri Ag. Ibrahim, Danda B. Rawat

    Published 2021
    “…Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. …”
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  4. 4
    Automated bilateral negotiation with incomplete information in the e-marketplace.

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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  5. 5
    Optimized tree-classification algorithm for classification of protein sequences

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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  6. 6
    Optimized tree-classification algorithm for classification of protein sequences

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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  7. 7
    DNA Words Based on an Enhanced Algorithm of Multi-objective Particle Swarm Optimization in a Continuous Search Space

    DNA Words Based on an Enhanced Algorithm of Multi-objective Particle Swarm Optimization in a Continuous Search Space by Selvan, K.V, Muhammad, M.S., Masra, S.M.W., Zuwairie, Ibrahim, Kian, Sheng Lim

    Published 2011
    “…The solution obtained from this algorithm is found to be better as compared with other approaches. …”
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  8. 8
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…A test suite of twelve benchmark test functions and three global optimization problems: Team Formation Optimization (TFO), Low Autocorrelation Binary Sequence (LABS), and Modified Condition/ Decision coverage (MC/DC) test case generation problem were solved using the proposed algorithm. …”
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  9. 9
    Biological-based semi-supervised clustering algorithm to improve gene function prediction

    Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

    Published 2011
    “…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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  10. 10
    Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems

    Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

    Published 2014
    “…The multiobjective fitness function use adaptive weight approach to assign weights to each objective for every generation based on objective improvement performance. …”
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  11. 11
    Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review

    Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review by Kauthar, Mohd Daud, Ananda, Ridho, Suhaila, Zainudin, Chan, Weng Howe, Moorthy, Kohbalan, Nurul Izrin, Md Saleh

    Published 2023
    “…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. …”
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  12. 12
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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  13. 13
    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem

    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

    Published 2022
    “…A test suite of twelve optimization benchmark test functions and three global optimization problems (Team Formation Optimization - TFO, Low Autocorrelation Binary Sequence - LABS, and Modified Condition/Decision Coverage - MC/DC test case generation) were solved using the proposed algorithm. …”
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  14. 14
    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…The transformation results in an equivalent mixed discrete optimization problem. The transformed problemis then decomposed into a bi-level optimization problem, which is solved using a combination of an efficient discrete filled function method identified earlier and a computational optimal control technique based on the concept of control parameterization. …”
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  15. 15
    Power-Constrained SOC Test Schedules through Utilization of Functional Buses

    Power-Constrained SOC Test Schedules through Utilization of Functional Buses by Hussin, Fawnizu Azmadi, Yoneda, Tomokazu, Orailoglu, Alex, Fujiwara, Hideo

    Published 2006
    “…The test schedule is composed of a set of test vector delivery sequences in small chunks, denoted as packets. The utilization of small packet sizes optimizes the functional bus utilization. …”
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  16. 16
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  17. 17
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  18. 18
    A study on component-based technology for development of complex bioinformatics software

    A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

    Published 2004
    “…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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  19. 19
    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam

    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

    Published 2023
    “…The monthly storage capacity fails in 2077, substantially earlier than the other three algorithms in Scenario 2. The LFWOA was used in this study to improve the efficacy of the algorithms by delivering a more accurate monthly storage capacity and reservoir risk assessment for Scenario 2 of RCP 2.6. …”
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  20. 20
    Multiple and solid data background scheme for testing static single cell faults on SRAM memories

    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. …”
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