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  1. 1

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

    Published 2012
    “…Factor analysis using principle component analysis (PCA) with an orthogonal rotation method, varimax factor rotation have resulted in 4 out of 15 parameters namely area, mean elevation, Gravelius factor and shape factor. …”
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    Thesis
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    Self-adaptive conjugate method for a robust and efficient performance measure approach for reliability-based design optimization by Keshtegar, Behrooz, Baharom, Shahrizan, El-Shafie, Ahmed

    Published 2018
    “…The advanced mean value and hybrid mean value methods are commonly used to evaluate the probabilistic constraint of reliability-based design optimization (RBDO) problems. …”
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    Article
  4. 4

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

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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    Thesis
  5. 5

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
  6. 6

    Optimization of super twisting sliding mode control gains using Taguchi method by Jamaludin, Zamberi, Chiew, Tsung Heng, Bani Hashim, Ahmad Yusairi, Rafan, Nur Aidawaty, Abdullah, Lokman

    Published 2018
    “…The optimization method applied a L9 orthogonal array and the performance index used was root mean square of tracking error and Fast Fourier Transform of control inputs. …”
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    Article
  7. 7

    Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

    Published 2024
    “…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. …”
    Article
  8. 8

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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    Thesis
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    Optimized subtractive clustering for cluster-based compound selection by Kuik, Sok Ping, Salim, Naomie

    Published 2006
    “…K-means produced the best results among the three clustering methods.…”
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    Conference or Workshop Item
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    Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm by Khalifa, Othman Omran, Wajdi, Muhammad H., Saeed, Rashid A., Hassan Abdalla Hashim, Aisha, Ahmed, Muhammed Z., Ali, Elmustafa Sayed

    Published 2022
    “…Specifically, the paper utilized the YOLOv5s architecture coupled with k-means algorithm to perform anchor box optimization under different illumination levels. …”
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    Article
  13. 13

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). …”
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    Research Report
  14. 14

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…Second of all, this study operates within experimental design with Taguchi method to discover the optimal design factors for the two proposed genetic operators. …”
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    Thesis
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    Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring by Moghbel, Mehrdad, Mashohor, Syamsiah, Mahmud, Rozi, Saripan, M. Iqbal

    Published 2016
    “…The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. …”
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    Article
  17. 17

    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

    Published 2010
    “…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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    Thesis
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    RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD by Homod R.Z., Mohamed Sahari K.S., Almurib H.A.F., Nagi F.H.

    Published 2023
    “…This modeling is achieved using a Takagi-Sugeno (TS) fuzzy model and tuned by Gauss-Newton method for nonlinear regression (GNMNR) algorithm. …”
    Article
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    Vibration analysis for early detection of bearing failures by Gam, Kheng Shiang

    Published 2024
    “…The vibration indicators utilized in this study include K-factor, root mean square (RMS) acceleration, peak acceleration, crest factor, kurtosis, RMS velocity, RMS displacement, and peak-to-peak displacement. …”
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    Final Year Project / Dissertation / Thesis
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    Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework by Aidil Zulkafli, Nadhirah, Elyca Anak Bundak, Caceja, Amiruddin Abd Rahman, Mohd, Chin Yap, Chi, Chong, Kok-Keong, Tee Tan, Sin

    Published 2024
    “…The accuracy of the prediction was controlled using the root-mean-square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2). …”
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    Article