Search Results - (( basic optimization learning algorithms ) OR ( using optimization based algorithm ))

Search alternatives:

Refine Results
  1. 1
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  2. 2
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  4. 4
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim

    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

    Published 2021
    “…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    Automated bilateral negotiation with incomplete information in the e-marketplace.

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  7. 7
    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system

    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system by M.H., Ali, Mohamad, Fadlizolkipi, Ahmad Firdaus, Zainal Abidin, Nik Zulkarnaen, Khidzir

    Published 2018
    “…However, the internal power parameters (weight and basis) of ELM are initialized at random, causing the algorithm to be unstable. The Particle swarm optimization (PSO) is a well-known meta-heuristic which is used in this research to optimize the ELM. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  8. 8
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Web Usage Mining for UUM Learning Care Using Association Rules

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    Web usage mining for UUM learning care using association rules

    Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

    Published 2004
    “…With the powerful of data mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E�Learning portal. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection

    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

    Published 2019
    “…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Neural Network – A Black Box Model

    Neural Network – A Black Box Model by Kuok, Kuok King, Chan, Chiu Po, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said, Chin Mei, Yun

    Published 2024
    “…A variety of metaheuristic algorithms have been used to train ANN, including Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO), Tabu Search (TS), and Harmony Search (HS). …”
    Get full text
    Get full text
    Get full text
    Book Chapter
    Save to List
    Saved in:
  14. 14
    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective

    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
    “…This survey paper is focused on the discussion of best optimal path routing algorithms in wireless sensor networks by using supervised machine learning approaches. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  15. 15
    An Optimized Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO) for cryptocurrency forecasting

    An Optimized Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO) for cryptocurrency forecasting by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Saeed, Faisal

    Published 2019
    “…However, forecasting result using basic SVM algorithms does not really promising. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  16. 16
    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems

    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

    Published 2010
    “…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Mean of correlation method for optimization of affective states detection in children

    Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

    Published 2018
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Improving neural networks training using experiment design approach

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…There are several methods of selecting training data from input space for neural networks which include D-optimal and Max-min design approaches. Consider a function approximation problem (Neural Network using Radial Basic Function structure) and limit the amount of training data, say (m) from N amount of possible data. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    CFD modeling on coal properties towards the burnout efficiency

    CFD modeling on coal properties towards the burnout efficiency by Nabil Asyraf Abd Halim

    Published 2024
    text::Final Year Project
    Save to List
    Saved in:
  20. 20
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

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

    Published 2006
    “…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: