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  1. 1

    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

    Published 2021
    “…Due to this developing significance of crop yield prediction, this article provides an exhaustive review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction. …”
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    Article
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    Development of an intelligent prediction tool for rice yield based on machine learning techniques by Md. Sap, Mohd. Noor, Awan, A. M.

    Published 2006
    “…This paper presents work on developing a software system for predicting rice yield from climate and plantation data. …”
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    Article
  4. 4

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

    Published 2006
    “…This paper presents work on developing a software system for predicting crop yield from climate and plantation data. …”
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    Conference or Workshop Item
  5. 5

    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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    Article
  6. 6

    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
    “…A multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model. …”
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    Article
  7. 7

    elopment of Neural Network Model for Predicting Crucial Product Properties or Yield for Optimisation of Refinery Operation by Mohamad, Sharliza

    Published 2005
    “…The objectives of this project are to develop a framework for the application of neural network modeling in predicting refinery product yield and properties, to develop neural network model for three case studies (predicting crude distillation yield, diesel pour point and hydrocracker total gasoline yield) and to evaluate the suitability of using neural networkmodelingfor predicting refinery product yield and properties. …”
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    Final Year Project
  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 by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

    Published 2023
    “…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. …”
    Article
  9. 9

    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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    Conference or Workshop Item
  10. 10

    Extreme gradient boosting (XGBoost) regressor and shapley additive explanation for crop yield prediction in agriculture by Dennis A/L Mariadass, Ervin Gubin Moung, Maisarah Mohd Sufian, Ali Farzamnia

    Published 2022
    “…Machine Learning can help anticipate yields more accurately. This paper proposes to use the XGBoost model for annual crop yield prediction in Malaysia. …”
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    Proceedings
  11. 11

    Predictive Analytics in Genetic Engineering as an Optimization Problem by Okewu, Emmanuel, Okewu Kehinde, Bukola

    Published 2024
    “…Also, the predictive outcomes of the computational simulation that was implemented in Python programming indicate that these local cultivars are developing drought-tolerant genetic variability. …”
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    Article
  12. 12

    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
    “…Owing to this great interest in the predictions, the study aims to develop a genetic algorithm (GA) to identify the relevant variables and search for the best combinations for modelling to examine the potential of oil palm production in Sarawak and Sabah, Borneo, Malaysia, under a given set of assumptions. …”
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    Article
  13. 13

    Predicting customer churn in telecommunication service provider industry using Random Forest / Wan Muhammad Naqib Zafran Wan Roslan by Wan Roslan, Wan Muhammad Naqib Zafran

    Published 2023
    “…This project addresses the challenge of customer churn in the Telecommunications Service Provider (TSP) industry by focusing on the Random Forest algorithm for predictive modeling. This study aims to throughly explore the Random Forest algorithm, develop a robust Random Forest customer churn predictive model, and evaluate its performance in predicting customer churn within the internet service provider sector. …”
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    Thesis
  14. 14

    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

    Published 2019
    “…This research presents the development of a GA and SW as a variables selection method in ANN and NARX models for predicting oil palm yield and output energy. …”
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    Thesis
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    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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    Article
  17. 17

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

    Published 2006
    “…Advance changes in technology, economy and business environment are influencing all sectors including agriculture.Rice as the worlds main dietary food is experiencing a decrease in yield due to the infection of pests and diseases, decreasing level of water sources, the scarcity of suitable land for agriculture and inefficient labour management.Rice Yield losses of approximately 31.5% were attributed to rice plant related diseases.This work describes the development of a connectionist model to predict the rice yield based on the amount of area infected by rice diseases.The Back Propagation learning algorithm were used with 5 input parameters which represents the planting seasons; the plantation district and the 3 main deadly disease recordings from the Muda Agricultural area in Malaysia during various planting seasons from 1995-2001. …”
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    Monograph
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    Bat algorithm and neural network for monthly streamflow prediction by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

    Published 2023
    “…The applications of artificial intelligence (AI) have been proved to have better performance as compared to conventional statistical method in streamflow prediction. Therefore, this study proposed on the development of streamflow prediction model AI techniques namely Bat algorithm (BA) and backpropagation neural network (BPNN). …”
    Conference Paper
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    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…s T-method (T-method) is a predictive modeling technique developed by Dr. Genichi Taguchi under the Mahalanobis-Taguchi system to predict unknown output or future state based on multivariable input variables. …”
    Conference paper
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    Analysis and Optimization of Ultrasound-Assisted Alkaline Palm Oil Transesterification by RSM and ANN-GA by Sajjadi, B., Davoody, M., Abdul Raman, Abdul Aziz, Ibrahim, Shaliza

    Published 2017
    “…The obtained results were then predicted by an optimized artificial neural network-genetic algorithm (ANN-GA) algorithm. …”
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    Article