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  1. 1
    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising

    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

    Published 2013
    “…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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  2. 2
    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
    “…The problem was initially tackled by “exact methods” such as the branch and bound method, which is based on the exhaustive enumeration of a restricted region of solutions containing exact optimal solutions. …”
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  3. 3
    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture

    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

    Published 2010
    “…It is shown that the computational complexity of proposed FAST-QR detection algorithm is approximately 48 % lower than the conventional QR decomposition detection algorithm. …”
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  4. 4
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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  5. 5
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  6. 6
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  7. 7
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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  8. 8
    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems

    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…This study presents three new low-discrepancy sequences named WELL sequence, Knuth sequence, and Torus sequence to initialize the population in the search space. …”
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  9. 9
    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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  10. 10
    HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD

    HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD by NGO , THI PHUONG THUY

    Published 2016
    “…This metadology way uses an algorithm which combines Pinch Design Method and Differential Evolution Method. …”
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  11. 11
    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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  12. 12
    Design and development of high performance swa cell design for local DNA sequence alignment

    Design and development of high performance swa cell design for local DNA sequence alignment by Syed Abdul Rahman, Syed Abdul Mutalib Al Junid

    Published 2017
    “…This study proposed three new DNA sequence alignment accelerator system cell design and architecture based on the Smith-Waterman Algorithm (SWA) named as the new Optimized SWA Linear Gap Penalty (OSL), Optimized SWA Affine Gap Penalty (OSA), and Optimized Recursive Variable Expansion SWA Linear Gap Penalty (ORSL). …”
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  13. 13
    Sequence t-way test generation using the barnacles mating optimizer algorithm

    Sequence t-way test generation using the barnacles mating optimizer algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2021
    “…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. …”
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  14. 14
    Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

    Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Zahari, Taha, Farzad, Tahriri, Siti Zawiah, Md Dawal

    Published 2014
    “…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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  15. 15
    Design and development of optimal path trace back using graph theory technique for accelerate DNA sequence alignment accelerator: article

    Design and development of optimal path trace back using graph theory technique for accelerate DNA sequence alignment accelerator: article by Othman, Nor Shuhaida

    Published 2010
    “…This paper presents the improvement of Smith-Waterman algorithm in comparing between two DNA sequence alignments. …”
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  16. 16
    Optimization of Assembly Sequence Planning Using Soft Computing Approaches: A Review

    Optimization of Assembly Sequence Planning Using Soft Computing Approaches: A Review by Muhammad Arif, Abdullah, M. F. F., Ab Rashid, Z., Ghazalli

    Published 2019
    “…This review focused on ASP modeling approach, optimization algorithms and optimization objectives. …”
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  17. 17
    Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method

    Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method by Hammadi, Ahmed Sahib

    Published 2016
    “…The results obtained by using the DE method were compared with those obtained by genetic algorithm (GA) method. …”
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  18. 18
    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm

    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

    Published 2023
    “…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
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  19. 19
    Multi-objective optimization of two-stage thermo-electric cooler using differential evolution: MO optimization of TEC using DE

    Multi-objective optimization of two-stage thermo-electric cooler using differential evolution: MO optimization of TEC using DE by Khanh, D.V.K., Vasant, P.M., Elamvazuthi, I., Dieu, V.N.

    Published 2015
    “…In this chapter, the technical issues of two-stage TEC were discussed. After that, a new method of optimizing the dimension of TECs using differential evolution to maximize the cooling rate and coefficient of performance was proposed. …”
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  20. 20
    An Assembly Sequence Planning Approach with a Multi-State Particle Swarm Optimization

    An Assembly Sequence Planning Approach with a Multi-State Particle Swarm Optimization by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2016
    “…In this paper, an approach based on a new variant of Particle Swarm Optimization Algorithm (PSO) called the multi-state of Particle Swarm Optimization (MSPSO) is used to solve the assembly sequence planning problem. …”
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