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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review by Sulaiman, Ahmad S. S., Wayayok, Aimrun, Aziz, Samsuzana A., Yun, Wong Mui, Leifeng, Guo

“…This paper presents a review on algorithm development and crop water modelling with a focus on optimizing significant parameters related to crop factors, soil factors, and weather factors. …”
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The development of robust and fast response control algorithm for UAV crop duster by Abas, M. F., Ahmad, Hamzah, Saad, N. Md, Pebrianti, Dwi, Mohd Rizal, Arshad

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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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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

“…The GA-ANN and GA-NARX models perform markedly better than the other models in the most training algorithms with different numbers of hidden layers.…”
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Weeds detection for agriculture using Convolutional Neural Network (CNN) algorithm / Khairun Nisa Mohammad Nasir by Mohammad Nasir, Khairun Nisa

“…As a result, this study has achieved 89.82% from the 80-20 split using CNN algorithm with an F1 score of 88.08%. The research then goes on to assess how well the CNN model generalizes to various agricultural environments that support multiple crop situations. …”
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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

“…This paper proposes to use the XGBoost model for annual crop yield prediction in Malaysia. …”
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Smart agriculture: precision farming through sensor-based crop monitoring and control system by Mohamad Hakhrani, Asyful Azhim, Abdul Hamid, Syamsul Bahrin

“…Subsequently, four distinct algorithms are trained with the collected dataset to ascertain the most optimal algorithm for predicting crop growth and harvesting time, resulting in the selection of the Random Forest Regression model, which attains the highest model score of 86%. …”
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Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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GIS-Enhanced Crop Yield Modeling with Machine Learning by Venkatesh, S.D., Chitra, K., Harilakshami, V.M.

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Reservoir system modelling using nondominated sorting genetic algorithm in the framework of climate change by Nurul Nadrah Aqilah, Tukimat

“…Model A is a combination methods of SDSM with M-CM, hydrological and crop model which considered the climate change variation. …”
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A spatial decision support system framework for optimization of cropping pattern and water resources allocation at pasargard plains, fars province, Iran by Ghasemi, Mohammad Mehdi

“…A unit response matrix groundwater model was coupled with a modified version of Genetic Algorithm (GA) in order to optimize cropping patterns and water allocation decisions. …”
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Modeling and Optimization of Water�Food�Energy Nexus for Malaysia�s Agricultural Sector by Siah, Q., Zabiri, H.

“…Hence, this paper aims to develop the first systematic and integrated model for optimal planning of resource allocation in Malaysiaâ��s agricultural sector. …”
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Modeling and Optimization of Water�Food�Energy Nexus for Malaysia�s Agricultural Sector by Siah, Q., Zabiri, H.

“…Hence, this paper aims to develop the first systematic and integrated model for optimal planning of resource allocation in Malaysiaâ��s agricultural sector. …”
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Modeling and Optimization of Water�Food�Energy Nexus for Malaysia�s Agricultural Sector by Siah, Q., Zabiri, H.

“…Hence, this paper aims to develop the first systematic and integrated model for optimal planning of resource allocation in Malaysiaâ��s agricultural sector. …”
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Applying multi-objective genetic algorithm (MOGA) to optimize the energy inputs and greenhouse gas emissions (GHG) in wetland rice production by Elsoragaby, S., Yahya, A., Mahadi, M.R., Nawi, N.M., Mairghany, M., M Elhassan, S.M., Kheiralla, A.F.

“…The developed multi-objective genetic algorithm (MOGA) model, showed an excess of energy inputs used by the farmers more than the required energy by 37.8 and 40 for the transplanting and broadcast seeding methods. …”
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Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

“…A machine learning algorithms, SVM have been used to build species identification models. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Cornsense: leaf disease detection application / Iffah Fatinah Mohamad Nasir by Mohamad Nasir, Iffah Fatinah

“…The purpose of this project is to develop a mobile application for corn leaf disease detection leveraging the YOLOv8 (You Only Look Once version 8) object detection algorithm. …”
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Development Of An Intelligent Water Blending System For Irrigation Of Crops With Various Salinity Tolerance And Aquaculture by Abdullah Al-Jughaiman, Abdullah Sulaiman

“…The water from two source tanks (one saline groundwater, and the other fresh water) is mixed inside the sink tanks to provide the required salinity in each tank and consequently reduce the fresh water consumption. A mathematical model for water blending was developed to simulate mixing water in a network of tanks. …”
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Lettuce Leaf Disease Detection Using Convolutional Neural Network Algorithm by NGU, SU HANG

“…The detection algorithm will be develop based on a modified AlexNet model. …”
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