Search Results - (( variable activation function algorithm ) OR ( based application designing algorithm ))

Search alternatives:

Refine Results
  1. 1
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations

    Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

    Published 2022
    “…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    Design of artificial intelligence based speed estimator for DC drives / Pauziah Saleh

    Design of artificial intelligence based speed estimator for DC drives / Pauziah Saleh by Saleh, Pauziah

    Published 2006
    “…For this purpose, the Lavenberg-Marquardt back propagation algorithm was used. A standard three layer feed-forward neural network with tan-sigmoid (tansig) activation functions in the hidden layer and purelin at the output layer is used for this test. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  5. 5
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

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

    Published 2018
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system

    Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system by Ghani, Muhamad Fadli

    Published 2023
    “…The proposed control strategy was designed with the switching function modification based on an FL approach in the conventional SMC algorithm called FLSMC. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  7. 7
    Design of Artificial Neural Network (ANN) based rotor speed estimator for DC drives / Siti Mutrikah Abd Mokhsin

    Design of Artificial Neural Network (ANN) based rotor speed estimator for DC drives / Siti Mutrikah Abd Mokhsin by Abd Mokhsin, Siti Mutrikah

    Published 2002
    “…This report describes the design of ANN based rotor speed estimator for separately excited DC motor. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

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

    Published 2004
    “…The extraction network is composed of rough neurons that accounts for the upper and lower approximations and embeds a membership function to replace ordinary activation functions. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Assessment of proposed lateral resistance system used with framed structures

    Assessment of proposed lateral resistance system used with framed structures by Fateh, Amir

    Published 2016
    “…Numerous studies have been conducted, specifically in structural engineering, to develop and evaluate the dynamic performance of energy dissipation systems based on the variable stiffness concept, such as active, semi-active, and passive variable stiffness methods. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    Development of optimized maintenance scheduling model for coal-fired power plant boiler

    Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

    Published 2023
    “…Generally, optimization computational and mathematical methods are designed for finding the best solution of a certain problems that aiming for minimizing or maximizing the objective functions based on the variables and subject to a set of constraints. …”
    text::Thesis
    Save to List
    Saved in:
  11. 11
    Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement

    Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement by Abdul Rahman, Nor Farahaida

    Published 2016
    “…Utilization of soft-computing algorithms in the operation of Shunt Active Power Filters (SAPFs) becomes a latest trend. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Real time De-mixing system based on LMS adaptive algorithm for blind two source signals separation

    Real time De-mixing system based on LMS adaptive algorithm for blind two source signals separation by Mehrkanoon, S., Moghavvemi, M., Fariborzi, H.

    Published 2007
    “…The time variant mixing matrix based on random vector with time variable elements are made. Several simulations obtain optimum results of implemented algorithm. …”
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  13. 13
    MotionSure: a cloud-based algorithm for detection of injected object in data in motion

    MotionSure: a cloud-based algorithm for detection of injected object in data in motion by Islam, Thouhedul, Olanrewaju, Rashidah Funke, Khalifa, Othman Omran

    Published 2017
    “…Mostly, the Man In The Middle (MITM) attack happens in this stage by hijacking active session variables, manipulating files and objects. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  14. 14
    A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments

    A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A. H., M. S. A., Radzak, Musa, Mailah, Nukman, Yusoff, Abd Razak, Bushroa, Mohd Sayuti, Ab. Karim, Ameen, Wadea, Jabbar, Waheb A., Alsewari, Abdulrahman A., Rassem, Taha H., Abdullah Nasser, Mohammed Abdullah, Abdulghafor, Rawad

    Published 2021
    “…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments

    A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A. H., Radzak, Muhammad S. A., Mailah, Musa, Yusoff, Nukman, Abd Razak, Bushroa, Ab.Karim, Mohd Sayuti, Ameen, Wadea, Jabbar, Waheb A., Alsewari, Abdulrahman A., Rassem, Taha H., Nasser, Abdullah B., Abdulghafor, Rawad

    Published 2021
    “…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments

    A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A.H., Radzak, Muhammad S.A., Mailah, Musa, Yusoff, Nukman, Abd Razak, Bushroa, Ab. Karim, Mohd Sayuti, Ameen, Wadea, A. Jabbar, Waheb, Alsewari, AbdulRahman A., Rassem, Taha H., Nasser, Abdullah B., Abdulmolla Abdulghafor, Rawad Abdulkhaleq

    Published 2021
    “…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance

    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2019
    “…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Forecasting particulate matter concentration using linear and non-linear approaches for air quality decision support

    Forecasting particulate matter concentration using linear and non-linear approaches for air quality decision support by Abdullah S., Ismail M., Ahmed A.N., Abdullah A.M.

    Published 2023
    Article
    Save to List
    Saved in:
  19. 19
    Analysis of boiler operational variables prior to tube leakage fault by artificial intelligent system

    Analysis of boiler operational variables prior to tube leakage fault by artificial intelligent system by Al-Kayiem, H.H., Al-Naimi, F.B.I., Amat, W.N.B.W.

    Published 2014
    “…The results showed that the NN with two hidden layers performed better than one hidden layer using Levenberg-Maquardt training algorithm. Moreover, it was noticed that hyperbolic tangent function for input and output nodes performed better than other activation function types. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  20. 20
    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus

    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

    Published 2016
    “…Logistic regression model has long been known and it is commonly used in analysing a binary outcome or dependent variable and connects the binary dependent variable to several independent variables. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: