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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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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

“…In this paper, we formulate a crop planning problem as a multiobjective optimization model and try to solve two different versions of the problem using two different optimization algorithms MCA and NSGA. …”
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An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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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

“…Crop yield predictions are carried out to estimate higher crop yield through the use of machine learning algorithms which are one of the challenging issues in the agricultural sector. …”
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Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development by Kehinde, Okewu, Emmanuel, Okewu, Wong, Ling Shing, Siti Sarah, Maidin

“…To demonstrate the practicality of using artificial intelligence (AI) to address these problems, the genetic algorithm is applied to genetic engineering (genetic mutation) of cowpea in a crop improvement program to generate useful bioinformatic information for further improvement of the crop. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Disease detection of solanaceous crops using deep learning for robot vision by Ahmad Radzi, Syafeeza, A.Halim, Nurul Hidayah, Abd Razak, Norazlina, Mohd Saad, Wira Hidayat, Wong, Yan Chiew, Amsan, Azureen Naja

“…Even the farmers have difficulty detecting crop diseases using their naked eyes due to several similar crop diseases. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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UAV-based weed detection in Chinese cabbage using deep learning by Ong, Pauline, Soon Teo, Kiat, Sia, Chee Kiong

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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Genetic Mutation of Cowpea as a Constrained Stochastic Optimization Problem in Sustainability by Emmanuel, Okewu, Kehinde, Okewu, Siti Sarah, Maidin, Wong, Ling Shing

“…However, uncertainties surround the genetic engineering process, potentially making genetic mutation for sustainability a constrained stochastic optimization (CSO) problem. Using series of experiments in Python programming, we applied genetic algorithm to the genetic mutation of cowpea, a tropical leguminous plant and protein-rich crop. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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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

“…Hence, weeds should be efficiently differentiated from the crops for the smart spraying solution. In this study, the Convolutional Neural Network (CNN) was used to perform weed detection amongst the commercial crop of Chinese cabbage, using the acquired images by Unmanned Aerial Vehicles. …”
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