Search Results - predicting roles difference ((optimization algorithm) OR (optimisation algorithm))

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  1. 1

    Metaheuristic algorithms applied in ANN salinity modelling by Khudhair, Zahraa S., Zubaidi, Salah L., Dulaimi, Anmar, Al-Bugharbee, Hussein, Muhsen, Yousif Raad, Putra Jaya, Ramadhansyah, Mohammed Ridha, Hussein, Raza, Syed Fawad, Ethaib, Saleem

    Published 2024
    “…The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). …”
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  2. 2

    A hybrid feature selection framework for predicting students performance by Zaffar, M., Hashmani, M.A., Habib, R., Quraishi, K.S., Irfan, M., Alqhtani, S., Hamdi, M.

    Published 2021
    “…There are different feature selection algorithms for predicting the performance of students, however the studies reported in the literature claim that there are different pros and cons of existing feature selection algorithms in selection of optimal features. …”
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  3. 3

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…This study examines the utilization of different Machine Learning algorithms, such as Linear Regression, Decision Trees, Support Vector Machines (SVM), Gradient Boosting, Random Forest, K-Nearest Neighbors (KNN), Convolutional Neural Network (CNN) Regression, and Particle Swarm Optimization (PSO), in the domain of predictive modeling and cost optimization in the field of construction project management. …”
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    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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    Thesis
  6. 6

    Development of genetic algorithm for optimization of yield models in oil palm production by Hilal, Yousif Y., Wan Ismail, Wan Ishak, Yahya, Azmi, Ash’aari, Zulfa Hanan

    Published 2018
    “…In the oil palm industry, modelling and selecting variables play a crucial role in apprehending different issues, i.e. decision making. …”
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  7. 7

    Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

    Published 2011
    “…The comparison between actual data from a different day and the prediction by the proposed method showed a match that is close enough to be considered as reliable. …”
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  8. 8

    Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation by Halabi, Laith M., Mekhilef, Saad, Hossain, Monowar

    Published 2018
    “…The proposed hybrid models include particle swarm optimization, genetic algorithm and differential evolution. …”
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    Article
  9. 9

    Predictive modelling of nanofluids thermophysical properties using machine learning by Olanrewaju, Alade Ibrahim

    Published 2021
    “…The optimization of the machine learning parameters was conducted using the Genetic Algorithm or the Bayesian Optimization Algorithm techniques. …”
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    Thesis
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    Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization by Nader Ibrahim Namazi, Sameer Alshehri, Rawan Bafail, Bader Huwaimel, Amal M. Alsubaiyel, Ali H. Alamri, Ahmed D. Alatawi, Hossam Kotb, Mohd Sani Sarjadi, Md. Lutfor Rahman, Mohammed A.S. Abourehab

    Published 2022
    “…In this technology, solubility plays an incontrovertible role. Therefore, achieving more knowledge about the development of promising numerical/computational methods of solubility prediction to validate the experimental data may be advantageous for increasing the quality of research and therefore, the efficacy of novel drugs. …”
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    Article
  13. 13

    Optimization of flood inundation simulation using multi-resolution Digital elevation model by Abdul Kadir, Muhammad Azraie

    Published 2022
    “…In this study, the relationship between DEM resolution and flood inundation prediction was determined in an attempt to propose a new optimization method of flood inundation prediction. …”
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    Thesis
  14. 14

    Machine learning for accelerating development of ion conducting membranes for fuel cell applications by Nasef, Mohamed Mahmoud, Habaebi, Mohamed Hadi

    Published 2025
    “…Moreover, the key ML algorithms for ion exchange membranes (IEMs) development techniques together with available ML frameworks and their potential uses in optimization of membranes structural properties, performance prediction, and new materials discovery are discussed. …”
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    Advancing Predictive Maintenance: Median-Based Particle Filtering in MOSFET Prognostics by Hadi E.F., Baharuddin M.Z.B., Zuhdi A.W.M.

    Published 2025
    “…In particular, the prediction of RUL plays a crucial role in MOSFET devices for many applications to prevent failures and maintenance schedule optimization. …”
    Article
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    Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam by Muhammad Aizat , Zainal Alam

    Published 2023
    “…In this regard, it was found that a vast majority of individuals exhibit mental accounting behaviour (66% of total respondents weight the prospect of gains and losses differently), where it was also found that future income wealth category, such as retirement savings, have most predictive weightage on retirement satisfaction based on an artificial neural network model (ANN) with an accuracy rate of 80.33%. …”
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    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…However, the most popular backpropagation algorithm which is based on Widrow-Hoff delta learning rule is not completely robust in the presence of outliers and this may cause false prediction of future values. …”
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