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  1. 1
    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
    “…The algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield. …”
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  2. 2
    Data-driven rice yield predictions and prescriptive analytics for sustainable agriculture in Malaysia

    Data-driven rice yield predictions and prescriptive analytics for sustainable agriculture in Malaysia by Marong, Muhammad, Husin, Nor Azura, Zolkepli, Maslina, Affendey, Lilly Suriani

    Published 2024
    “…A comprehensive dataset for rice yield prediction in Malaysia was constructed, encompassing yield data from 2014 to 2018. …”
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  3. 3
    Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester

    Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester by Moghaddam, Mansour Ghaffari, Ahmad @ Amat, Faujan, Basri, Mahiran, Abdul Rahman, Mohd Basyaruddin

    Published 2010
    “…The root mean squared error (RMSE), coefficient of determination (R2) and absolute average deviation (AAD) between the actual and predicted yields were determined as 0.0335, 0.9999 and 0.0647 for training set, 0.6279, 0.9961 and 1.4478 for testing set and 0.6626, 0.9488 and 1.0205 for validation set using quick propagation algorithm (QP).…”
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  4. 4
    A framework for predicting oil-palm yield from climate data

    A framework for predicting oil-palm yield from climate data by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2006
    “…This paper presents work on developing a software system for predicting crop yield, for example oil-palm yield, from climate and plantation data. …”
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  5. 5
    Predicting crop yields using a new robust Bayesian averaging model based on multiple hybrid ANFIS and MLP models: Predicting crop yields using a new robust Bayesian averaging model

    Predicting crop yields using a new robust Bayesian averaging model based on multiple hybrid ANFIS and MLP models: Predicting crop yields using a new robust Bayesian averaging model by Bazrafshan O., Ehteram M., Dashti Latif S., Feng Huang Y., Yenn Teo F., Najah Ahmed A., El-Shafie A.

    Published 2023
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  6. 6
    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.

    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…This paper presents our work on developing an intelligent system for predicting crop yield, for example oil-palm yield, from climate and plantation data. …”
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  7. 7
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  8. 8
    Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow

    Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

    Published 2023
    “…It is concluded that the means of machine learning have great potential for the application to predict oil palm yield using weather and soil moisture data. � 2022 by the authors. …”
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  9. 9
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  10. 10
    Artificial neural network method modeling of microwave-assisted esterification of PFAD over mesoporous TiO2‒ZnO catalyst

    Artificial neural network method modeling of microwave-assisted esterification of PFAD over mesoporous TiO2‒ZnO catalyst by Soltani, Soroush, Shojaei, Taha Roodbar, Khanian, Nasrin, Shean, Thomas Yaw Choong, Asim, Nilofar, Yue, Zhao

    Published 2022
    “…The esterification reaction conditions predicted by ANN showed to be potential for modeling and predicting FAME yield with an extremely well precision of 97.06%.…”
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  11. 11
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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  12. 12
    Modelling the yield loss of oil palm due to Ganoderma Basal Stem Rot disease

    Modelling the yield loss of oil palm due to Ganoderma Basal Stem Rot disease by Assis Kamu

    Published 2016
    “…Based on mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), BMA model has the lowest values, thus selected as the best model for oil palm yield loss. …”
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  13. 13
    A connectionist model to predict rice yield based on disease infection

    A connectionist model to predict rice yield based on disease infection by Kamaruddin, Siti Sakira

    Published 2006
    “…The output parameter represents the rice yield measured in kilograms per hectare.The result of the model shows that the recorded average mean deviation is 0.053.…”
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  14. 14
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Clustering is one of the means in data mining of predicting the class based on separating the data categories from similar features. …”
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  15. 15
    Modelling the yield loss of oil palm due to ganoderma basal stem rot disease

    Modelling the yield loss of oil palm due to ganoderma basal stem rot disease by Assis bin Kamu

    Published 2016
    “…Based on mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), BMA model has the lowest values, thus selected as the best model for oil palm yield loss. …”
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  16. 16
    Yield prediction of supercritical fluid extraction of Nigella sativa using neutral networks / Sarah Diana Isnin and Sitinoor Adeib Idris

    Yield prediction of supercritical fluid extraction of Nigella sativa using neutral networks / Sarah Diana Isnin and Sitinoor Adeib Idris by Isnin, Sarah Diana, Adeib Idris, Sitinoor

    Published 2025
    “…A feed-forward multi-layer neural network with Levenberg-Marquardt training algorithm was developed to predict yield for supercritical carbon dioxide (SC-CO2) extraction of Nigella sativa essential oil. …”
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  17. 17
    Application of artificial neural network for yield prediction of lipase-catalyzed synthesis of dioctyl adipate

    Application of artificial neural network for yield prediction of lipase-catalyzed synthesis of dioctyl adipate by Abdul Rahman, Mohd Basyaruddin, Chaibakhsh, Naz, Basri, Mahiran, Salleh, Abu Bakar, Raja Abdul Rahman, Raja Noor Zaliha

    Published 2009
    “…In this study, an artificial neural network (ANN) trained by backpropagation algorithm, Levenberg–Marquadart, was applied to predict the yield of enzymatic synthesis of dioctyl adipate. …”
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  18. 18
    Optimisation and performance evaluation of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the prediction of biogas production from palm oil mill effluent (POME)

    Optimisation and performance evaluation of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the prediction o... by Chong, D.J.S., Chan, Y.J., Arumugasamy, S.K., Yazdi, S.K., Lim, J.W.

    Published 2023
    “…Results demonstrated that these models were well aligned with two years of operational data with high coefficient of determination (R2) of up to 0.98. ANFIS yields the highest prediction accuracy, with R2 of 0.9791 along with the lowest mean absolute error (MAE) of 0.0730 and root mean squared error (RMSE) of 0.1438. …”
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  19. 19
    Development of genetic algorithm for optimization of yield models in oil palm production

    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
    “…Across the optimization, procedures obtained the best Two Factor Interaction (2FI) models to achieve the best model of oil palm productivity prediction with a value of R2 of 0.948, mean squared error of 0.022, and the model P-value of < 0.0001 in Sabah. …”
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  20. 20
    Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction

    Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

    Published 2021
    “…This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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