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Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem by Jarin, Sams, Khatun, Mst Khaleda, Shafie, Amir Akramin

“…We investigate these algorithms here as a linear crop planning model and use them to acquire the maximum total gross margin according with minimum total working capital in order to satisfy some constraints. …”
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A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms by Ghazvini, Anahita, Mohd Sharef, Nurfadhlina, Balasundram, Siva Kumar, Lee, Lai Soon

“…This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and regression algorithms to create a digital twin for farmers to augment the concentration and composition prediction-based crop nutrient recovery. …”
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A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms by Mohd Sharef, Nurfadhlina, Balasundram, Siva Kumar, Lai, Soon Lee, Ghazvini, Anahita

“…This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and re-gression algorithms to create a digital twin for farmers to augment the concentration and compo-sition prediction-based crop nutrient recovery. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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How can aerial imagery and vegetation indices algorithm can be used for monitoring crop through geotagged system? A review by Kumaran, Vikneswaran Jeya, Mohidem, Nur Adibah, Che’ya, Nik Norasma, Wan Ilahi, Wan Fazilah, Arif Shah, Jasmin, Yusof, Norhakim

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How Can Aerial Imagery and Vegetation Indices Algorithms Be Used for Monitoring CropsThrough Geotagged System? A Review by Vikneswaran Jeya Kumaran, Nur Adibah Mohidem, Nik Norasma Che’Ya, Wan Fazilah Wan Ilahi, Jasmin Arif Shah, Norhakim Yusof

UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterativ Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Ong, Pauline, Soon Teo, Kiat, Sia, Chee Kiong

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Pauline Ong, Pauline Ong, Kiat Soon Teo, Kiat Soon Teo, Chee Kiong Sia, Chee Kiong Sia

“…The acquired images were preprocessed and subsequently segmented into the crop, soil, and weed classes using the Simple Linear Iterative Clustering Superpixel algorithm. …”
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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

“…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

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

“…The aim of the study is to propose and establish a sustainable and long term reservoir operation system and management with adaptation to climate change using the integrated models. The models are Nondominated Sorting Genetic Algorithm type II (NSGA-II), Linear Programming (LP), Statistical Downscaling Model (SDSM) with Multi-linear Correlation Matrix (M-CM), hydrological and crop models. …”
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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

“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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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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