Search Results - (( based selection methods algorithm ) OR ( risk optimization method algorithm ))

Search alternatives:

Refine Results
  1. 1
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

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

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Scaled Conjugate Gradient using strong Wolfe line search for portfolio selection / Nurfatihah Anizan

    Scaled Conjugate Gradient using strong Wolfe line search for portfolio selection / Nurfatihah Anizan by Anizan, Nurfatihah

    Published 2024
    “…Based on the results, the Scaled LAMR method is the most robust method among others as it can solve 100% of the test functions. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm

    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana

    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

    Published 2018
    “…In this paper, we use two-step features selection and Quality Threshold with Optimization methods to design anomaly-based HIDS and NIDS separately. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    A Risk Assessment of Transmission Line Overload Based on MLSI/PSO

    A Risk Assessment of Transmission Line Overload Based on MLSI/PSO by Ruhaizad, Ishak, Ali, A., Nazir, Muhammad S., Malik, Muhammad Z.

    Published 2019
    “…Based on the traditional partial swarm optimization algorithm, the corresponding weights are selected according to the influence factors of each input quantity, and the calculation accuracy of the traditional point estimation method is improved to realize the overload risk assessment of transmission lines. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  9. 9
    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff

    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff by Md Ariff, Norharyati

    Published 2007
    “…For the image segmentation, genetic algorithm are use to segment the bone image and it is a new method that applies in the image processing field. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Agustina Pertiwi, Dwika Ananda, Subhan, Subhan, Jumanto, Jumanto, Dasril, Yosza, swanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Agustina Pertiwi b, Dwika Ananda, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    An enhanced supplier selection model based on optimized analytic network process towards sustainable information technology outsourcing

    An enhanced supplier selection model based on optimized analytic network process towards sustainable information technology outsourcing by Fusiripong, Prashaya

    Published 2022
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements

    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements by Ramadhan, Mazen Farid Ebrahim

    Published 2022
    “…Moreover, the improvements of different QoS metrics values achieved by using a minimum-weight-based multi-objective algorithm (MOS-MWO) for scheduling scientific workflows are better than those of the previous work which used the Pareto optimization method. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk

    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

    Published 2019
    “…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Much Aziz Muslim, Much Aziz Muslim, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi b, Dwika Ananda Agustina Pertiwi b, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Dwika Ananda Agustina Pertiwi b, Dwika Ananda Agustina Pertiwi b, Subhan b, Subhan b, Jumanto, Jumanto, Nikmah, Tiara Lailatul, Agustina Pertiwi, Dwika Ananda, Iswanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: