Search Results - (( yield prediction model algorithm ) OR ( _ application ((bee algorithm) OR (tree algorithm)) ))

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  1. 1

    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
    “…Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
    Article
  2. 2

    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

    Published 2021
    “…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. …”
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    Article
  3. 3

    Automated Fruit and Flower Counting using Digital Image Analysis by Hoo, Zhou Yang

    Published 2015
    “…The purpose of this project is to predict the yield of fruit and flowers. The ability to predict the yield would benefit the farmers as they plan the sale, the shipment and operations. …”
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    Final Year Project / Dissertation / Thesis
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  5. 5

    Improved tree routing protocol in zigbee networks by Al-Harbawi, Mostafa Kamil Abdulhusain

    Published 2010
    “…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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    Thesis
  6. 6

    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

    Published 2024
    “…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. …”
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    Thesis
  7. 7

    Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

    Published 2025
    “…The evaluation of the three models for predicting compressive strength yielded interesting results: The Decision Tree (DT) model demonstrated the best performance, with a relatively low Mean Squared Error (MSE) of 5.125 and Mean Absolute Error (MAE) of 1.642, and a high R² value of 0.918, indicating that the model explains approximately 91.8% of the variance in the target variable. …”
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    Article
  8. 8

    Near-infrared spectroscopy modeling of combustion characteristics in chip and ground biomass from fast-growing trees and agricultural residue by Shrestha, Bijendra, Posom, Jetsada, Pornchaloempong, Pimpen, Sirisomboon, Panmanas, Shrestha, Bim Prasad, Ariffin, Hidayah

    Published 2024
    “…The optimal model was selected by evaluating the coefficients of determination in the prediction set (R2P), root mean square error of prediction (RMSEP), and RPD values. …”
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    Article
  9. 9

    Enhanced faster region-based convolutional neural network for oil palm tree detection by Liu, Xinni

    Published 2021
    “…Oil palm trees are important economic crops in Malaysia. One of the audit procedures is to count the number of oil palm trees for plantation management, which helps the manager predict the plantation yield and the amount of fertilizer and labor force needed. …”
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    Thesis
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    Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

    Published 2019
    “…Unmanned aerial vehicles (UAV) have been recently deployed in the agriculture sector for various applications such as crop monitoring and yield prediction in order to achieve the precise agriculture objectives. …”
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    Thesis
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    Predicting wheat yield from 2001 to 2020 in Hebei Province at county and pixel levels based on synthesized time series images of Landsat and MODIS by Zhang, Guanjin, Roslan, Siti Nur Aliaa, Mohd Shafri, Helmi Zulhaidi, Zhao, Yanxi, Wang, Ci, Quan, Ling

    Published 2024
    “…And the regression algorithm had a more prominent effect on yield prediction, while the yield prediction model using Long Short-Term Memory (LSTM) outperformed the yield prediction model using Light Gradient Boosting Machine (LGBM). …”
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    Article
  14. 14

    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2024
    “…These results suggest that the new T-method prediction model is better in predicting the output even when only 4 features incorporated in the model…”
    Conference Paper
  15. 15

    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
  16. 16

    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
  17. 17

    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
  18. 18

    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
  19. 19

    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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    Article
  20. 20

    An Intelligent Hybrid Model Using CNN and RNN for Crop Yield Prediction by JUNE, KHOO YAN

    Published 2023
    “…In this study, an intelligent hybrid model using CNN and RNN for crop yield prediction is proposed. …”
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    Final Year Project Report / IMRAD