Search Results - (( using function methods algorithm ) OR ( its application tools algorithm ))

Refine Results
  1. 1

    A modified discrete filled function algorithm for solving nonlinear discrete optimization problems by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan

    Published 2012
    “…The discrete filled function method is a global optimization tool for searching for best solution amongst multiple local optima.This method has proven useful for solving large-scale discrete optimization problems.In this paper, we consider a standard discrete filled function algorithm in the literature and then propose a modification to increase its efficiency.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2

    Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants by Chua, Eng Wee, Goh, Chian Siang

    Published 2019
    “…Predictive algorithms are important tools for translating genomic data into meaningful functional annotations. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    The development of semantic meta-database: an ontology based semantic integration of biological databases by Samsudin, Ruhaidah, Deris, Safaai, Othman, Muhammad Razib, Md. Illias, Rosli

    Published 2007
    “…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
    Get full text
    Get full text
    Monograph
  4. 4

    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
  5. 5
  6. 6

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Mohd Sharif, Zakaria, Mohammad Fadhil, Abas, Fatimah, Dg Jamil, Norhafidzah, Mohd Saad, Addie, Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Optimization of multi-holes drilling toolpath using tiki-taka algorithm by Norazlina, Abdul Rahman

    Published 2024
    “…The research methodology involves problem modeling, algorithm development, and validation. The TSP concept formulated the MDMT problem, representing holes as cities and tools as a salesman in finding the shortest path to develop a mathematical model or fitness function. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Zakaria, Mohd Sharif, Abas, Mohammad Fadhil, Dg Jamil, Fatimah, Mohd Saad, Norhafidzah, Hashim, Addie Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  9. 9

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
    Get full text
    Get full text
    Thesis
  11. 11

    Utility-based non-cooperative power control game in wireless environment / Yousef Ali Mohammed Al-Gumaei by Yousef Ali, Mohammed Al-Gumaei

    Published 2017
    “…Novel utility and cost functions proposed in this work are the method to derive efficient distributed power control algorithms. …”
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12

    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
  13. 13

    Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system by Nasir, Ahmad Nor Kasruddin, Abdul Razak, Ahmad Azwan

    Published 2022
    “…It has the theory of diversification and intensification in its strategy, which allows the algorithm to present itself as a good deterministic type of optimization tool to solve various engineering problems. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    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
  15. 15

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
    Get full text
    Get full text
    Thesis
  16. 16
  17. 17

    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

    Published 2024
    “…The proposed algorithm, named Intelligent Water Drops with Simulated Annealing (IWDSA), combines two powerful optimization methods: Intelligent Water Drops (IWD) and Simulated Annealing (SA). …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

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

    Published 2014
    “…The first category includes premier methods such as Response Surface Methodology (RSM) and Taguchi method and the second one includes newer methods like hybrid methods of ANNs and Genetic Algorithm (GA). …”
    Get full text
    Get full text
    Thesis
  19. 19

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). In designing the network, a combination of back propagation or generalized delta learning rule with sigmoid transfer function has been used. …”
    Get full text
    Get full text
    Thesis