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  1. 1
    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed

    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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  2. 2
    Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm

    Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
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  3. 3
    A modified π rough k-means algorithm for web page recommendation system

    A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

    Published 2018
    “…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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  4. 4
    Power-efficient wireless coverage using minimum number of uavs

    Power-efficient wireless coverage using minimum number of uavs by Sawalmeh A., Othman N.S., Liu G., Khreishah A., Alenezi A., Alanazi A.

    Published 2023
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  5. 5
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…Using Landsat Thematic Mapper (TM) and ModisIAster Airborne Simulator (hMSTER) images as the test datasets, the BBSI algorithm was compared to the Optimum Index Factor (OIF) algorithm in selection of the best three-band combination for image visualization. …”
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  6. 6
    Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster

    Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster by Ali, Wala'a Hussein

    Published 2018
    “…The algorithms applied separately with (1) Mean (2) Median (3) Mode (4) Geometric mean (5) Harmonic mean. …”
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  7. 7
    Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map

    Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map by Sumiati, .

    Published 2023
    “…The test results of the MCM Method gave a Mean Squared Error (MSE) of 0.65 and Root Mean Squared Error (RMSE) of 0.80 and the test results of the CCM Method with a Mean Squared Error (MSE) of 0.15 and a Root Mean Squared Error (RMSE) of 0.39. …”
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  8. 8
    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…Filtered-X least mean square (FXLMS) control algorithm is a conventional algorithm employed to cancel the noise in linear environment. …”
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  9. 9
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…As one of the alternative forecasting methods to forecast MH-ELD, 1-factor WeSuSFTS model has less mean absolute percentage error than M-factors WeSuSFTS model and two other conventional FTS models. …”
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  10. 10
    Predicting factor of online purchasing behaviour among university students in UiTMCT / Mohd Fadzlee Mazlan

    Predicting factor of online purchasing behaviour among university students in UiTMCT / Mohd Fadzlee Mazlan by Mazlan, Mohd Fadzlee

    Published 2022
    “…Several prediction rules already been produced with high interestingness by using K-Mean clustering algorithm and Random Tree algorithm. …”
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  11. 11
    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction

    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction by Tan, James Yiaw Beng

    Published 2012
    “…We propose a model known as K-means-Greedy Algorithm (KGA) model in this research to overcome this serious drawback of the BP network. …”
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  12. 12
    Self-adaptive conjugate method for a robust and efficient performance measure approach for reliability-based design optimization

    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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  13. 13
    Multi-scene design analysis of integrated energy system based on feature extraction algorithm

    Multi-scene design analysis of integrated energy system based on feature extraction algorithm by Huang, Sihua, Mohd Ali, Noor Azizi, Shaari, Nazlina, Mat Noor, Mohd Sallehuddin

    Published 2022
    “…Finally, according to the given feature vectors, the feature clustering models of various energy loads are established by using K-means clustering algorithm, and the load forecasting results of multi-energy systems are obtained. …”
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  14. 14
    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
    “…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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  15. 15
    Gradient auto-tuned Takagi-Sugeno Fuzzy Forward control of a HVAC system using predicted mean vote index

    Gradient auto-tuned Takagi-Sugeno Fuzzy Forward control of a HVAC system using predicted mean vote index by Homod R.Z., Sahari K.S.M., Almurib H.A.F., Nagi F.H.

    Published 2023
    “…The TS model is first trained offline using Gauss-Newton Method for Nonlinear Regression (GNMNR) algorithm with data collected from both building and HVAC system equipments. …”
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  16. 16
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

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

    Published 2024
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  17. 17
    An intelligent system based on kernel methods for crop yield prediction

    An intelligent system based on kernel methods for crop yield prediction by Majid Awan, A., Md. Sap, Mohd. Noor

    Published 2006
    “…For this purpose, a robust weighted kernel k-means algorithm incorporating spatial constraints is presented. …”
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    Conference or Workshop Item
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  18. 18
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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  19. 19
    Optimization of super twisting sliding mode control gains using Taguchi method

    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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  20. 20
    Application of multilayer perceptron with backpropagation algorithm and regression analysis for long-term forecast of electricity demand: A comparison

    Application of multilayer perceptron with backpropagation algorithm and regression analysis for long-term forecast of electricity demand: A comparison by Bong, David B L, Tan, J.Y.B., Lai, K.C.

    Published 2009
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