Search Results - (( effective classification problems algorithm ) OR ( using optimization model algorithm ))

Search alternatives:

Refine Results
  1. 1
    A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification

    A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

    Published 2024
    “…Secondly, an improved CatBoost algorithm (EBGWO-CatBoost) was proposed, which was a combination of improved GWO algorithm (EBGWO) and CatBoost algorithm, and the optimized GWO algorithm was used to offset the defects of CatBoost algorithm in parameter tuning. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength

    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

    Published 2015
    “…The ANFIS optimized by AMBA is used employed to model classification of Malaysian small medium enterprises (SMEs) based on strength using non-financial factors. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol

    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

    Published 2023
    “…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
    Get full text
    Get full text
    Student Project
    Save to List
    Saved in:
  4. 4
    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Furthermore, the original DA is only suitable for solving continuous optimization problems. Although there is a binary version of the algorithm, it cannot be directly used for solving discrete optimization problems like the Traveling Salesman Problem (TSP). …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  5. 5
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO

    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  7. 7
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    Modified anfis architecture with less computational complexities for classification problems

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection

    A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection by Noor Syahirah, Nordin, Mohd Arfian, Ismail

    Published 2023
    “…In this paper, BOA was improvised by combining this algorithm with Harmony Search (HS) in order to achieve optimal results in fuzzy modelling. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    An ensemble of neural network and modified grey wolf optimizer for stock prediction

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    A novel performance metric for building an optimized classifier

    A novel performance metric for building an optimized classifier by Hossin, Mohammad, Sulaiman, Md. Nasir, Mustapha, Aida, Mustapha, Norwati

    Published 2011
    “…Problem statement: Typically, the accuracy metric is often applied for optimizing the heuristic or stochastic classification models. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    A new model for iris data set classification based on linear support vector machine parameter's optimization

    A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Spam classification based on supervised learning using grasshopper optimization algorithm and artificial neural network

    Spam classification based on supervised learning using grasshopper optimization algorithm and artificial neural network by Mumtazimah, Mohamad, Engku Fadzli Hasan, Syed Abdullah, Ghaleb, S.A.A., Ghanem, W.A.H.M.

    Published 2021
    “…Evaluation of its performance was performed on an often-used standard dataset. The results showed that the proposed MLP model trained by GOA achieves high accuracy of up to 94.25% performance compared to other optimization.…”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  18. 18
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    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
    “…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: