Search Results - (( developing function method algorithm ) OR ( learning active learning algorithm ))

Refine Results
  1. 1

    Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm by Zainuddin, Zarita

    Published 2001
    “…In this thesis, factors that govern the learning speed of the backpropagation algorithm are investigated and mathematically analyzed in order to develop strategies to improve the performance of this neural network learning algorithm. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…To recognize and classify the level of jogging intensity, k-Nearest Neighbours (k-NN) algorithms will be considered as a machine learning method. …”
    Get full text
    Get full text
    Get full text
    Academic Exercise
  4. 4

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…The work is further extended to developing and integrating the idea of active control of flexible structures into an interactive learning environment. …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    E-Handrawn Calculator by Mohamad, Syamimi

    Published 2008
    “…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
    Get full text
    Get full text
    Final Year Project
  6. 6

    A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato... by Alsa’Di, Kawthar, Nik Long, Nik Mohd Asri

    Published 2025
    “…This technique uses the Adaptive Moment Estimation Method (Adam) as an optimization algorithm with feed-forward deep learning to minimize the error function and training the model using five layers with different activation functions. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…Particularly, GA is utilized to determine the optimal number of hidden layers, number of neurons in each hidden layer, type of training algorithm, type of activation function of hidden and output neurons, initial weight, learning rate, momentum term, and epoch size of a multilayer feed-forward ANN. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Three algorithms of Linear (PURELIN), hyperbolic tangent sigmoid (TANSIG) and logistic sigmoid (LOGSIG) activation functions were selected for output layer. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions by Alsa’di, Kawthar, Nik Long, Nik Mohd Asri, Senu, Norazak, Eshkuvatov, Z.K.

    Published 2025
    “…A hybrid technique, combining a polynomial neural network (PNN) with an extreme learning machine algorithm without using any activation functions, is developed. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

    Published 2020
    “…Convolution Neural Network (CNN) using deep learning algorithm is chosen in identifying frequency of movement and execution time of housebreaking crime. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
    Get full text
    Get full text
    Article
  13. 13

    Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah by Abdullah, Nur Raudzah

    Published 2020
    “…Existing researches on air pollution forecasting used a variety of machine learning algorithm. One of the popular algorithms used to forecast the air pollution is Artificial Neural Network (ANN). …”
    Get full text
    Get full text
    Thesis
  14. 14

    Extreme Learning Machine neural networks for multi-agent system in power generation by Yaw C.T., Wong S.Y., Yap K.S., Tan C.H.

    Published 2023
    “…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”
    Article
  15. 15

    Development of an Isolated Digit Speech Recognition Based on Multilayer Perceptron Model by Mohamad Hussin, Ummu Salmah

    Published 2004
    “…A typical or fixed sigmoid function method is used in learning phase. In the recognition phase, an adaptive sigmoid function is employed. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

    Published 2025
    “…A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…The hierarchical fuzzy clustering algorithm developed in this work assign the overlapping structures (structures having more than one activity) to more than one clusters if their fuzzy membership values are significantly high for those clusters. …”
    Get full text
    Get full text
    Monograph
  18. 18

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…A novel feature extraction algorithm was developed to extract the feature vectors. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Improving modified cocomo ii artificial neural network using hyperbolic tangent activation function by Abdulaziz Al-Shalif, Sarah Abdulkarem

    Published 2017
    “…Back-propagation learning algorithm is applied to the multilayer neural network for training and testing. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    Stress mental health symptom assessment mobile application for young adults by Lee, Chun Hoong

    Published 2023
    “…Before this stage, the KNN algorithm is employed to construct the model using Google Form response data as part of the application development process. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis