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  1. 1

    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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    Article
  2. 2

    Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

    Published 2018
    “…The proposed algorithm is capable of selecting the optimal feature subsets while improving the recognition of acceleration activity using a minimum number of features. …”
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    Article
  3. 3

    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

    Published 2026
    “…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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    Article
  4. 4

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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    Thesis
  5. 5

    Voltage constrained optimal power flow based using genetic algorithm by Yassir Asnawi, Teuku Hasannuddin

    Published 2015
    “…Effectiveness of the proposed method was tested on IEEE 30 bus system and it has been compared to other optimization of power fl ow using other methods, for example the Evolutionary Programming (EP), Differential Evolution (DE) and Particle Swarm Optimization (PSO) methods. …”
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    Article
  6. 6

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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    Thesis
  7. 7

    LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model by Dashti, Maedeh, Gandoman, Taghi Javdani, Adeh, Dariush Hasanpoor, Zulzalil, Hazura, Md Sultan, Abu Bakar

    Published 2021
    “…Then, MMRE, PRED (0.25), and MdMRE criteria have been used to evaluate and compare the proposed method against other evolutionary algorithms. …”
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    Article
  8. 8

    Dynamic smart grid communication parameters based cognitive radio network by Haider H.T., Muhsen D.H., Shahadi H.I., See O.H., Elmenreich W.

    Published 2023
    “…A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
    Article
  9. 9

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    Published 2011
    “…Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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    Article
  10. 10

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

    Published 2013
    “…Genetic Algorithms (GA) which is based on biological evolution is one of the metaheuristics that has been successfully applied to JSSP. …”
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    Thesis
  11. 11

    Direct Tuning Phase-Shift Angle In Dab Dc-Dc Converter Using Moth Flame Optimization (Mfo) Algorithm by Lo, Norman Kun King

    Published 2022
    “…Since the conventional tuning has a couple of downsides, mainly related to the time-consuming and inconsistence accuracy, the auto-tuning phase shift angle using Moth Flame Optimization (MFO) algorithm in DAB is proposed in this project. …”
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    Undergraduates Project Papers
  12. 12

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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    Thesis
  13. 13

    Development of a robust intelligent controller for a semi-active car suspension system by Abas, Hesham Ahmed Abdul Mutleba

    Published 2022
    “…Commonly, the Fuzzy rules are optimized using offline optimization methods such as Differential Evolutionary (DE), Particle Swarms Optimization (PSO), or Artificial Neural Network (ANN) algorithms. …”
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    Thesis
  14. 14

    An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

    Published 2023
    “…The model proposed in this research is based on clustering of students using K-means algorithm and the course of content delivery is adaptively characterized for each student using Hidden Markov Models. …”
    Conference Paper
  15. 15

    Base pressure control through micro jets at supersonic Mach numbers using experimental and machine learning approach by Aabid, Abdul, Khan, Sher Afghan, Yasir, Javed

    Published 2026
    “…Furthermore, machine learning (ML) algorithms were utilized to predict base pressure outcomes and optimize control strategies. …”
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    Article
  16. 16

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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    Conference or Workshop Item
  17. 17

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The problem of determining simultaneously the model order and coefficient of an Autoregressive Moving Average (ARMA) model is examined in this paper. An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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    Proceeding Paper
  18. 18

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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  19. 19

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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    Article
  20. 20

    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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    Article