Search Results - (( developing function method algorithm ) OR ( data evaluation using algorithm ))

Refine Results
  1. 1

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Lastly, the extended tree-based method for categorical data sets is developed and evaluated. …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Pashto language stemming algorithm by Aslamzai, Sebghatullah, Saidah Saad

    Published 2015
    “…Furthermore, the accuracy and strength of the proposed algorithm is evaluated using word count method. To validate the function of the developed algorithm, two native speakers of Pashto were recruited to evaluate the algorithm in terms of its accuracy and strength. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm by Othman, Mahmod, Khalid, Shaiful Annuar, Abdullah, Fader, Amir Hamzah, Shezrin Hawani, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…Finally, an algorithm is developed for automatic evaluation of external validity measures on the generated variant multiclass clustering results. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Hybrid subjective evaluation of rule Exraction Algorithm using Weighted Subsethood-Based (WSBA) by Othman, Mahmod, Ku-Mahamud, Ku Ruhana, Hawani, Shezrin, Hamzah, Amir, Khalid, Shaiful Annuar, Abdullah, Fader

    Published 2013
    “…Fuzzy rules are important elements that being highlighted in any fuzzy expert system.This research proposes the framework of subjective performance evaluation using fuzzy technique for ranking the performance of the financial performance of a company under a multi criteria environment.There are a lot of techniques used such as fuzzy similarity function, fuzzy synthetic decision and satisfaction function have been adopted.The framework is based on fuzzy multi-criteria decision-making that consists of fuzzy rules.The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…The designed algorithms are implemented for EHD equations and their performance is evaluated by using different performance indicators. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

    Published 2015
    “…Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
    Get full text
    Get full text
    Thesis
  10. 10

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
    Get full text
    Get full text
    Thesis
  11. 11

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

    Published 2018
    “…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12

    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…The proposed EHGSO methodology based on the adaptive damping BHHH technique (EHGSOAdBHHH) is tested on Single Diode (SD), and Double Diode (DD) PV models using actual experimental data. EHGSOAdBHHH exhibits outstanding accordance with attained experimental data compared with other algorithms, and its superiority is validated using several statistical criteria.…”
    Get full text
    Get full text
    Article
  13. 13

    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm by Mohd Tumari, Mohd Zaidi Mohd, Mustapha, Nik Mohd Zaitul Akmal, Ahmad, Mohd Ashraf, Saat, Shahrizal, Ghazali, Mohd Riduwan

    Published 2023
    “…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14

    Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

    Published 2024
    “…Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications by Sabry, Ahmad H., Wan Hasan, Wan Zuha, Ab Kadir, M. Zainal A., Mohd Radzi, Mohd Amran, Shafie, Suhaidi

    Published 2018
    “…The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
    Get full text
    Get full text
    Get full text
    Academic Exercise
  17. 17

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Total of ten control methods determined from population and individual data were tested against another 10 healthy persons to evaluate the algorithm performance. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

    Published 2020
    “…From the accuracy test, SVM are proven to be one of the best classifier to classify the image data. For the future work, this system need to be improved by using dataset that are related to the ASD and by using other classification algorithm.…”
    Get full text
    Get full text
    Thesis
  19. 19

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  20. 20

    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

    Published 2017
    “…The whole constraint analyzer and the fitness function were combined with four SBTs (genetic algorithm, evolutionary algorithm, simulating annealing, and quantum genetic algorithm). …”
    Get full text
    Get full text
    Get full text
    Thesis