Search Results - (( java implementation path algorithm ) OR ( using classifier machine algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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2
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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3
Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Article -
4
Comparative study of machine learning algorithms in data classification
Published 2025“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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Final Year Project / Dissertation / Thesis -
5
Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Final Year Project -
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Cyberbullying detection: a machine learning approach
Published 2022“…Bag of Words model was used to convert text into numerical inputs. The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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Final Year Project / Dissertation / Thesis -
7
Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer
Published 2018“…In this paper, three machine-learning algorithms (Support Vector Machine, K-nearest neighbors, and Decision tree) have been used and the performance of these classifiers has been compared in order to detect which classifier works better in the classification of breast cancer. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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9
Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain
Published 2020“…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
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10
Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…When a fall event occurs, the real-time data is collected and placed in a *.CSV file. Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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Proceeding Paper -
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A comparative analysis of predicting heart disease using machine learning algorithms
Published 2026“…This study applies six machine learning algorithms, including K-nearest neighbors, logistic regression, Bayesian classifier, decision tree, random forest, and support vector machine. …”
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Conference or Workshop Item -
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Integrating finance dictionary in lexicon-based approach with machine learning algorithm to analyse the impact of OPEC news sentiment on financial market / Wu Ling
Published 2020“…The labelled sentences are then used to train the supervised machine learning classifiers. …”
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13
Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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Conference or Workshop Item -
14
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms
Published 2019“…Landsat 8 images of resolutions 15 x 15 m were used and classified via machine learning and non-machine learning algorithms. …”
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Article -
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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar
Published 2020“…Consequently, this study utilized a medium resolution remote sensing image, Sentinel-2 with 10-meter spatial resolution to classified the building in Selangor, Malaysia. In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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18
Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Academic Exercise -
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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Thesis -
20
Improving classification of EEG signals for a four-state brain machine interface
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Working Paper
