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  1. 1
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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  2. 2
    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network

    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
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  3. 3
    FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources

    FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources by Al-Qadhi, Abdulrahman K., Athauda, Rukshan, Latip, Rohaya, Hussin, Masnida

    Published 2026
    “…Function as a Service (FaaS) is becoming a popular method to process such IoT workloads. …”
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  4. 4
    A block cipher based on genetic algorithm

    A block cipher based on genetic algorithm by Zakaria, Nur Hafiza

    Published 2016
    “…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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  5. 5
    Design and implementation of MD5 hash function algorithm using verilog HDL

    Design and implementation of MD5 hash function algorithm using verilog HDL by Shamsiah, Suhaili, Niam, Cleopatra Chundang, Zainah, Md Zain, Norhuzaimin, Julai

    Published 2022
    “…Among hash algorithms, MD5 is the most used hash function algorithm. …”
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  6. 6
    Computing the autopilot control algorithm using predictive functional control for unstable model

    Computing the autopilot control algorithm using predictive functional control for unstable model by H. A., Kasdirin, J. A., Rossiter

    Published 2009
    “…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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  7. 7
    Effect of fitness function on localization performance in range-free localization algorithm

    Effect of fitness function on localization performance in range-free localization algorithm by Han, Fengrong, Izzeldin Ibrahim, Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue

    Published 2024
    “…How to choose the best localization fitness function for a specific target is a key factor in determining whether the localization algorithm is accurate or not. …”
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  8. 8
    A video-rate color image segmentation using adaptive and statistical membership function

    A video-rate color image segmentation using adaptive and statistical membership function by Sojodishijani, Omid, Rostami, Vahid, Ramli, Abdul Rahman

    Published 2010
    “…In this algorithm, statistical information of regions is used to create fuzzy membership functions in color model components. …”
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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
    Common benchmark functions for metaheuristic evaluation: a review

    Common benchmark functions for metaheuristic evaluation: a review by Hussain, Kashif, Mohd Salleh, Mohd Najib, Shi, Cheng, Naseem, Rashid

    Published 2017
    “…In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. …”
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  11. 11
    An efficient computation technique for cryptosystems based on Lucas functions

    An efficient computation technique for cryptosystems based on Lucas functions by Md Ali, Zulkarnain, Othman, Mohamed, Md. Said, Mohamad Rushdan, Sulaiman, Md. Nasir

    Published 2008
    “…We have found that the binary sequence used in a new algorithm is shorter than a special sequence used in an existing algorithm. …”
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  12. 12
    Design and Implementation of MDS Hash Function Algorithm Using Verilog HDL

    Design and Implementation of MDS Hash Function Algorithm Using Verilog HDL by Shamsiah, Suhaili, Cleopatra Chundang, Niam, Zainah, Md. Zain, Norhuzaimin, Julai

    Published 2020
    “…Among hash algorithms, MD5 is the most used hash function algorithm. …”
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  13. 13
    Transform of Artificial Immune System algorithm optimization based on mathematical test function

    Transform of Artificial Immune System algorithm optimization based on mathematical test function by Yaw M.W., Chong K.H., Kamil K.

    Published 2023
    Conference Paper
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  14. 14
    Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems

    Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems by Mansor, Nur Farraliza

    Published 2018
    “…This is achieved by using a first type of association between the linear increase function with a second model of the dynamic increase of step function being remarkable in other combinations and also other models.In conclusion,this proposed approach managed to generate a fairer roster and was thus capable of maximising the balancing distribution of shifts and routes among drivers,which contributed to the lowering of illness, incidents,absenteeism and accidents.…”
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  15. 15
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  16. 16
    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller

    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

    Published 2010
    “…A fuzzy logic is fully defined by its membership function. …”
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  17. 17
    A Proposed Method For Selecting The Clustering Algorithm In Radial Basis Function [QA223. A581 2008 f rb].

    A Proposed Method For Selecting The Clustering Algorithm In Radial Basis Function [QA223. A581 2008 f rb]. by Ang, Sau Loong

    Published 2008
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  18. 18
    Logic Programming In Radial Basis Function Neural Networks

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…To do that I used the root mean square error function and Schwarz bayesian criterion as model selection criteria. …”
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  19. 19
    Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah

    Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah by Hanafiah, Sukri

    Published 1997
    “…Optimal Layout is the layout of the arrangment of CMOS transistor with the implementation of a random logic functional on an array of CMOS transistor. …”
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  20. 20
    An efficient method for determining all the extreme points of function with one variable

    An efficient method for determining all the extreme points of function with one variable by Pandiya, Ridwan

    Published 2014
    “…The algorithm is the combination of the filled function's algorithm and Inner Iteration algorithm, called IRH's algorithm, in which Inner Iteration algorithm works at the domain which is usually ignored by filled function's algorithm.…”
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