Search Results - parallel prediction ((bees algorithm) OR (model algorithm))

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  1. 1
    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach

    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach by Quadros, Jaimon Dennis, Khan, Sher Afghan, T., Prashanth

    Published 2021
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  2. 2
    Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem

    Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem by Bahri, Susila

    Published 2004
    “…Forecasting model for short range weather prediction that is used here is the two level Barotropic models. …”
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  3. 3
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  4. 4
    Dengue outbreak prediction: hybrid meta-heuristic model

    Dengue outbreak prediction: hybrid meta-heuristic model by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin

    Published 2018
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  5. 5
    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…The central composite design (CCD) method was used to design the FEA experiment and establish the BKA-BPNN regression prediction model. The RMSE of this model’s training set and test set are 0.001615 and 0.0029328. …”
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  6. 6
    Mapreduce algorithm for weather dataset

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…Results from the proposed algorithm have been compared with the existing model known as AWK (Alfred Aho, Peter Weinberger, and Brian Kernighan) model. …”
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  7. 7
    MapReduce algorithm for weather dataset

    MapReduce algorithm for weather dataset by Majid, Mazlina A., Romli, Awanis, Ahmad, Noraziah, Hammad, Khalid Adam Ismail

    Published 2018
    “…Results from the proposed algorithm have been compared with the existing model known as AWK (Alfred Aho, Peter Weinberger, and Brian Kernighan) model. …”
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  8. 8
    Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin

    Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin by Che Wan Samsudin, Che Wan Sufia

    Published 2025
    “…Essential phases of the project include data collection, data preprocessing, and the implementation of the Particle Swarm Optimization-Random Forest price prediction algorithm. Both simulated and real-world experiments are used as a basis to rigorously test and validate the predictive capability of the model. …”
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  9. 9
    Leveraging data lake architecture for predicting academic student performance

    Leveraging data lake architecture for predicting academic student performance by Abdul Rahim, Shameen Aina, Sidi, Fatimah, Affendey, Lilly Suriani, Ishak, Iskandar, Nurlankyzy, Appak Yessirkep

    Published 2024
    “…In addition to forecasting the student performance, appropriate machine learning algorithms such as Support Vector Classifier, Naive Bayes, and Decision Trees are used to build prediction models by using the data lake's scalability and parallel processing capabilities. …”
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  10. 10
    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy

    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  11. 11
    Development of a real-time clutch transition strategy for a parallel hybrid electric vehicle

    Development of a real-time clutch transition strategy for a parallel hybrid electric vehicle by Vu, Trieu Minh

    Published 2011
    “…Model predictive control (MPC) has been used for this model and tested with different control horizons and weighting factors to verify the ability of MPC to control the vehicle speeds for the clutch engagement. …”
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  12. 12
    Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia

    Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia by Adli Zakaria M.N., Ahmed A.N., Abdul Malek M., Birima A.H., Hayet Khan M.M., Sherif M., Elshafie A.

    Published 2024
    “…In terms of different time horizons, the LSTM model was found to be more accurate than the MLP and XGBoost model when predicting 7 days ahead, demonstrating its superiority in capturing long-term dependencies. …”
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  13. 13
    Graphical user interface for surface roughness prediction of CNC milling machine / Muhammad Qayyum Nor Asffan

    Graphical user interface for surface roughness prediction of CNC milling machine / Muhammad Qayyum Nor Asffan by Nor Asffan, Muhammad Qayyum

    Published 2020
    “…It can function to analyse data, develop algorithms even create models and applications. In this research, MATLAB Graphical User Interface (GUI) is used to develop a user- friendly program that can predict surface roughness of Aluminium 6061 in CNC milling machine. …”
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  14. 14
    Integrated OBF-NN models with enhanced extrapolation capability for nonlinear systems

    Integrated OBF-NN models with enhanced extrapolation capability for nonlinear systems by H., Zabiri, M., Ramasamy, T. D. , Lemma, Maulud, Abdulhalim

    Published 2013
    “…This paper proposes a nonlinear system identification using parallel linear-plus-neural network models that provide more accurate predictions on the process behavior even on extrapolated regions. …”
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  15. 15
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  16. 16
    An integrated priority-based cell attenuation model for dynamic cell sizing

    An integrated priority-based cell attenuation model for dynamic cell sizing by Amphawan, Angela, Omar, Mohd Nizam, Din, Roshidi

    Published 2012
    “…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
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  17. 17
    Host Based Intrusion Detection and Prevention Model Against DDoS Attack in Cloud Computing

    Host Based Intrusion Detection and Prevention Model Against DDoS Attack in Cloud Computing by Jaber, Aws Naser, Mohamad Fadli, Zolkipli, Shakir, Hasan Awni

    Published 2018
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  18. 18
    Extended Kalman Filter (EKF)-based modular-stack Vanadium Redox Flow Battery (V-RFB) prediction model development for reducing electrode contact resistance and parallelization current

    Extended Kalman Filter (EKF)-based modular-stack Vanadium Redox Flow Battery (V-RFB) prediction model development for reducing electrode contact resistance and parallelization curr... by Mohamed, Mohd Rusllim

    Published 2019
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  19. 19
    Efficient Numerical Modelling of Extreme Wave

    Efficient Numerical Modelling of Extreme Wave by Tan , Vi Nie

    Published 2020
    “…Future works will be carried out to study the parallelization of the algorithm to allow for larger problem size to be treated.…”
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  20. 20
    Efficient Numerical Modelling of Extreme Waves

    Efficient Numerical Modelling of Extreme Waves by Tan, Vi Nie

    Published 2020
    “…Future works will be carried out to study the parallelization of the algorithm to allow for larger problem size to be treated.…”
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