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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

“…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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Rice yield prediction - a comparison between enhanced back propagation learning algorithms by Saad, Puteh, Jamaludin, Nor Khairah, Rusli, Nursalasawati, Bakri, Aryati, Kamarudin, Siti Sakira

“…In this study, we examine the performance of four enhanced BP algorithms to predict rice yield in MADA plantation area in Kedah, Malaysia. …”
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Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms by Puteh, Saad, Nor Khairah, Jamaludin, Nursalasawati, Rusli, Aryati, Bakri, Siti Sakira, Kamarudin

“…In this study, we examine the performance of four enhanced BP algorithms to predict rice yield in MAD A plantation area in Kedah, Malaysia. …”
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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.

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

“…The results showed that kernel NDVI (kNDVI) and near-infrared reflectance (NIRv) slightly outperform normalized difference vegetation index (NDVI) in yield prediction. 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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An intelligent system based on kernel methods for crop yield prediction by Majid Awan, A., Md. Sap, Mohd. Noor

“…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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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

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

“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.…”
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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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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.

“…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. …”

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

“…However, the outcome yielded a sub-optimal result as the orthogonal array has limitation involving a fixed and limited combination used and lack of higher order feature combination in the analysis. …”

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

“…Neural network modeling is an alternative approach to prediction using mathematical correlations. The project is an extension of a previous research conducted by the university on product yield and properties prediction using non-linear regression method. …”
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Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

“…There was not enough information available on the implementation of neural networks and genetic algorithm for the prediction and selecting input variables in oil palm yield and output energy. …”
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Predictive Analytics in Genetic Engineering as an Optimization Problem by Okewu, Emmanuel, Okewu Kehinde, Bukola

“…Such predictive analytics information is useful for guiding decision-making by researchers and breeders in the crop improvement program.…”
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An Intelligent Hybrid Model Using CNN and RNN for Crop Yield Prediction by JUNE, KHOO YAN

“…In this study, an intelligent hybrid model using CNN and RNN for crop yield prediction is proposed. …”
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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

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

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Accurate Real-TIme Object Tracking with Linear Prediction Method by P. Y., Yeoh, Syed Abu Bakar, Syed Abdul Rahman

“…Using a second order of the linear prediction method, the proposed algorithm is able to accurately track the moving object. …”
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Automated Fruit and Flower Counting using Digital Image Analysis by Hoo, Zhou Yang

“…The proposed algorithm includes image segmentation, size thresholding and shape analysis, counting of the regions of interest, and yield prediction. …”
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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

“…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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