Search Results - (( using functional based algorithm ) OR ( sequence optimization based 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
    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm

    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

    Published 2017
    “…In this article, we have proposed a distance-based sequence encoding algorithm that captures the sequence's statistical characteristics along with amino acids sequence order information. …”
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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
    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
    “…Hence, this research’s objective aimed to propose an optimization strategy based on Structural Modification and Optimizing Training Network for improving the lacking of accuracy of response in the chatbot application, to propose the algorithm enhancement to improve the current attention mechanism in the Attentive Sequence-to-Sequence model and the network’s training optimization of its inability to memorize the dialogue history, and lastly, to evaluate the accuracy of response of the proposed solution through data training on loss function and real data testing. …”
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  5. 5
    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
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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
    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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  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
    Iteration strategy and ts effect towards the performance of population based metaheuristics

    Iteration strategy and ts effect towards the performance of population based metaheuristics by Nor Azlina, Ab. Aziz, Nor Hidayati, Abdul Aziz, Azlan, Abd Aziz, Tasiransurini, Abdul Rahman, Wan Zakiah, Wan Ismail, Zuwairie, Ibrahim

    Published 2020
    “…This is an important issue to be considered when designing a new population-based metaheuristic. Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. …”
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  11. 11
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Abd Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  12. 12
    Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm

    Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm by Al-Qattan, Zakaria Noor Aldeen Mahmood

    Published 2010
    “…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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  13. 13
    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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  14. 14
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Ab. Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  15. 15
    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 algorithm used weight mapping crossover (WMX) and Insertion Mutation (IM) as genetic operators for sub-chromosomes represented with priority-based representation. …”
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  16. 16
    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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  17. 17
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  18. 18
    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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  19. 19
    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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  20. 20
    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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