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  1. 1
    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics

    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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  2. 2
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…Traditional data mining algorithms cannot be directly applied to educational problems, as they may have a specific objective and function. …”
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  3. 3
    Development of committee machine models for multiple response optimization problems

    Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

    Published 2014
    “…Four methodologies are to make four different CM models to solve MRO problems. The fifth methodology proposes the final algorithm which uses four CM models together to solve MRO problems. …”
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  4. 4
    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…To overcome the instability selection problem, a stability selection approach is put forward to enhance the performance of single-split variable selection method. …”
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  5. 5
    Predictive Analytics in Genetic Engineering as an Optimization Problem

    Predictive Analytics in Genetic Engineering as an Optimization Problem by Okewu, Emmanuel, Okewu Kehinde, Bukola

    Published 2024
    “…The nature of the problem requires that a stochastic optimization algorithm be applied in the metaheuristic search rather than using a deterministic or mathematical approach. …”
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  6. 6
    Attack path selection optimization with adaptive genetic algorithms

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…We have also carried out a comparative study on the performance of the adaptive GA used in this problem against the conventional GA. The results shows that attack graphs analyzed with the adaptive GA yields significantly better solutions. …”
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  7. 7
    Attack path selection optimization with adaptive genetic algorithms

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…We have also carried out a comparative study on the performance of the adaptive GA used in this problem against the conventional GA. The results shows that attack graphs analyzed with the adaptive GA yields significantly better solutions. …”
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  8. 8
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  9. 9
    An artificial bee colony-based double layered neural network approach for solving quadratic Bi-level programming problems

    An artificial bee colony-based double layered neural network approach for solving quadratic Bi-level programming problems by Watada, J., Roy, A., Wang, B., Tan, S.C., Xu, B.

    Published 2020
    “…The improved ABC algorithm accommodates upper-level decision problems by selecting a set of potential solutions from all combinations of solutions. …”
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  10. 10
    Application of correlation as a measure of performance

    Application of correlation as a measure of performance by Mohd. Rijal, O., Mohd Noor, N., Chang, Y.F.

    Published 2011
    “…A judicious use of this relationship may yield a measure of performance for a given algorithm. …”
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  11. 11
    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation

    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation by Din, Abdul Sattar

    Published 2013
    “…Simulation results have shown that despite the computational simplicity, the algorithm yields the percentage error of 0.033%, which is close to that of the EKF, which yields 0.028%, while the DR yields 0.125%. …”
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  12. 12
    Class binarization with self-adaptive algorithm to improve human activity recognition

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

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. 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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  13. 13
    Numerical analysis

    Numerical analysis by Butcher, John

    Published 2008
    “…Much of this knowledge is in the form of algorithms for solving certain standard and widely used problems. …”
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  14. 14
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The developed patterns are applied in the field of real-time analysis. Finally, the algorithm found, which would solve the image segmentation problem.…”
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  15. 15
    Flowfield-dependent variant method for moving-boundary problems

    Flowfield-dependent variant method for moving-boundary problems by Zulkafli, Mohd Fadhli, Omar, Ashraf A., Asrar, Waqar

    Published 2014
    “…The formulation itself yields a sparse matrix, which can be solved by using any iterative algorithm. …”
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  16. 16
    Development of a syncope classification algorithm from physiological signals acquired in tilt-table test

    Development of a syncope classification algorithm from physiological signals acquired in tilt-table test by Gan, Ming Hong

    Published 2023
    “…Aim of this study is to design an algorithm which able to classify syncope patient based on their physiological signal. …”
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  17. 17
    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network

    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

    Published 2009
    “…One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. In this research, a problem solving scenario for a metal cutting industry which faces some problems in determining the end product quality of Manganese Molybdenum (Mn-Mo) pressure vessel plate is investigated. …”
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  18. 18
    Efficient relay placement algorithm using landscape aware routing (erpalar)

    Efficient relay placement algorithm using landscape aware routing (erpalar) by Onabajo, Olawale Olusegun

    Published 2011
    “…ERP ALAR was implemented in Matlab R2009a using Genetic Algorithm (GA) with multi-objectives. GA is an optimization algorithm that simulates natural selection process as found in nature. …”
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  19. 19
    k-nearest neighbour using ensemble clustering based on feature selection approach to learning relational data

    k-nearest neighbour using ensemble clustering based on feature selection approach to learning relational data by Alfred, Rayner, Shin, Kung Ke, Sainin, Mohd Shamrie, On, Chin Kim, Pandiyan, Paulraj Murugesa, Ag Ibrahim, Ag Asri

    Published 2016
    “…However, DARA suffers a major drawback when the cardinalities of attributes are very high because the size of the vector space representation depends on the number of unique values that exist for all attributes in the dataset.A feature selection process can be introduced to overcome this problem.These selected features can be further optimized to achieve a good classification result.Several clustering runs can be performed for different values of k to yield an ensemble of clustering results. …”
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  20. 20
    Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong

    Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong by Karoon, Suksonghong

    Published 2014
    “…To overcome this difficulty, this study proposes the use of multi-objective evolutionary algorithms (MOEAs) that are applied in the field of engineering for solving the multi-objective MVS portfolio optimization problem. …”
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