Search Results - feed-forward ((((prediction algorithm) OR (evolution algorithm))) OR (selection algorithm))

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  1. 1
    A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction

    A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction by Yousif S.T., Ismail F.B., Al-Bazi A.

    Published 2025
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  2. 2
    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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  3. 3
    A channel quality indicator (CQI) prediction scheme using feed forward neural network (FF-NN) technique for MU-MIMO LTE system

    A channel quality indicator (CQI) prediction scheme using feed forward neural network (FF-NN) technique for MU-MIMO LTE system by Abdulhasan, Muntadher Qasim, Salman, Mustafa Ismael, Ng, Chee Kyun, Noordin, Nor Kamariah, Hashim, Shaiful Jahari, Hashim, Fazirulhisham

    Published 2014
    “…In this paper, a CQI prediction scheme using Feed Forward-Neural Network (FF-NN) algorithm for MU-MIMO-LTE Advanced systems is proposed. …”
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  4. 4
    Differential evolution for neural networks learning enhancement

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

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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  5. 5
    Forecasting solar power generation using evolutionary mating algorithm-deep neural networks

    Forecasting solar power generation using evolutionary mating algorithm-deep neural networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…The intricate nonlinear relationship between solar irradiation, ambient temperature, and module temperature is captured for accurate prediction. Additionally, the paper conducts a comprehensive comparison with established algorithms, including Differential Evolution (DE-DNN), Barnacles Mating Optimizer (BMO-DNN), Particle Swarm Optimization (PSO-DNN), Harmony Search Algorithm (HSA-DNN), DNN with Adaptive Moment Estimation optimizer (ADAM) and Nonlinear AutoRegressive with eXogenous inputs (NARX). …”
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  6. 6
    Nature-Inspired cognitive evolution to play Ms. Pac-Man

    Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

    Published 2011
    “…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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  7. 7
    Skin Hydration And Transepidermal Water Loss Measurement Using Vis/nir Spectroscopy And Feed-forward Backpropagation Neural Network

    Skin Hydration And Transepidermal Water Loss Measurement Using Vis/nir Spectroscopy And Feed-forward Backpropagation Neural Network by Tan, Chun Ho

    Published 2022
    “…Thus, this study proposed the use of visible/near-infrared (VIS/NIR) spectroscopy, specifically at wavelengths 698 nm, 970 nm, 1200 nm, 1450 nm, and 1950 nm to predict the skin hydration and TEWL. In this study, the prediction models were built using simple linear regression, multiple regression analysis, and feed-forward backpropagation neural network (FFBPNN) with gradient descent algorithm. …”
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  8. 8
    An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance

    An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance by Raheem, Ajiboye Adeleke

    Published 2016
    “…Feed-forward Neural Networks, is a multilayer perceptron and a network structure capable of modelling the class prediction as a nonlinear combination of the inputs. …”
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  9. 9
    Wind power prediction using Artificial Neural Network: article

    Wind power prediction using Artificial Neural Network: article by Edik, Septony

    Published 2010
    “…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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  10. 10
    Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game

    Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

    Published 2015
    “…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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  11. 11
    Wind power prediction using Artificial Neural Network

    Wind power prediction using Artificial Neural Network by Edik, Septony

    Published 2010
    “…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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  12. 12
    Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli

    Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli by Ahmad Zulkhairi , Zulkefli

    Published 2021
    “…For TG, the LM algorithm with a testing accuracy of 76.7%, sensitivity of 28.6% and specificity of 91.3% was selected. …”
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  13. 13
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
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  14. 14
    Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N. H. Idris ...[et al.]

    Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N.... by Idris, N. H., Salim, N. A., Othman, M. M., Yasin, Z. M.

    Published 2017
    “…The historical data obtained from NERC report is analyzed and being used in ANN for prediction purposed. This paper compares the supervised training algorithms of feed-forward neural network with backpropagation include Lavenberg- Marquadt (LM), Scale Conjugate Gradient (SCG) and Quasi Newton Backpropagation (BFG). …”
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  15. 15
    Predicting remaining useful life of rotating machinery based artificial neural network

    Predicting remaining useful life of rotating machinery based artificial neural network by Mahamad, Abd Kadir, Saon, Sharifah, Hiyama, Takashi

    Published 2010
    “…The ANN RUL prediction uses FeedForward Neural Network (FFNN) with Levenberg Marquardt of training algorithm. …”
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  16. 16
    Early detection of dengue disease using extreme learning machine

    Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

    Published 2018
    “…Therefore, this research proposed an improved algorithm known as ELM which is an extension of Feed Forward Neural Network that utilize the Moore Penrose Pseudoinver matrix that gain the optimal weights of neural network architecture. …”
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  17. 17
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    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
    “…ANN can be categorized into three main types: single layer, recurrent network and multilayer feed-forward network. In multilayer feed-forward ANN, the actual performance is highly dependent on the selection of architecture and training parameters. …”
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  18. 18
    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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  19. 19
    Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data

    Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data by Ajiboye, Adeleke Raheem, Ruzaini, Abdullah Arshah, Qin, Hongwu

    Published 2015
    “…Feed-forward, Back Propagation (BP) Network is a network structure capable of modeling the class prediction as a nonlinear combination of the inputs. …”
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  20. 20
    Evolution strategies for evolving artificial neural networks in an arcade game

    Evolution strategies for evolving artificial neural networks in an arcade game by Tse, Guan Tan, Teo, Jason, Anthony, Patricia

    Published 2010
    “…The aim of this paper is to use a simple but powerful evolutionary algorithm called Evolution Strategies (ES) to evolve the connection weights and biases of feed-forward artificial neural networks (ANN) and to examine its learning ability through computational experiments in a non-deterministic and dynamic environment, which is the well-known arcade game called Ms. …”
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