Search Results - yield prediction algorithm

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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Backpropagation algorithm for rice yield prediction by Puteh, Saad, Mohamed Rizon, Mohamed Juhari, Nor Khairah, Jamaludin, Siti Sakira, Kamarudin, Aryati, Bakri, Nursalasawati, Rusli

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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

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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.

“…As the next step, correlation and regression analysis is applied for analyzing the impact of various parameters on the rice yield. and also for predicting the yield.…”
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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.

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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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

“…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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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

“…A multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

“…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…”

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

“…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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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.

“…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. Machine learning algorithms are capable of learning linear and nonlinear patterns in complex agro-meteorological data. …”

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

“…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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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

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

“…Refinery optimisation requires accurate prediction of crucial product properties and yield of desired products. …”
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Predictive Analytics in Genetic Engineering as an Optimization Problem by Okewu, Emmanuel, Okewu Kehinde, Bukola

“…In the search for drought-tolerant cowpea, this study applied a genetic algorithm as a predictive analytics tool in the genetic engineering of three native cowpea landraces (Dan muzakkari, Gidigiwa, and Dan mesera) selected from Northern Nigeria (specifically from Kontagora in Niger State of Nigeria). …”
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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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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

“…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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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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