Search Results - (( developing building vector algorithm ) OR ( java implementation learning algorithm ))

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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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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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

“…The information of building features especially in the urban area is very important to support urban management and development. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm – support vector regression model by Alade, Ibrahim Olanrewaju, Bagudu, Aliyu, Oyehan, Tajudeen A., Abd Rahman, Mohd Amiruddin, Saleh, Tawfik A., Olatunjif, Sunday Olusanya

“…Methods: These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).Results:The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10−4 and 4.62 × 10−4 for oxygenated and deoxygenated hemoglobin, respectively. …”
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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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Investigating the application of artificial intelligence for earthquake prediction in Terengganu by Marhain S., Ahmed A.N., Murti M.A., Kumar P., El-Shafie A.

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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Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

“…The main objectives for this project are focusing on the development of user interface that can connect with the machine learning build in Microsoft Azure for pump diagnostic purpose. …”
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Automated essay grading system / Cheong Tau Pau by Cheong, Tau Pau

“…The secondary objective is to compare the efficiency of the nearest neighbor algorithm and the vector space model. Reviews on system and algorithm are done to obtain more information about developing the system. …”
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Energy consumption prediction by using machine learning for smart building: Case study in Malaysia by M. Shapi, Mel Keytingan, Nor Azuana, Ramli, Awalin, Lilik J.

“…Three methodologies which are Support Vector Machine, Artificial Neural Network, and k-Nearest Neighbour are proposed for the algorithm of the predictive model. …”
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Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

“…This study adopted supervised machine learning algorithm which is the Support Vector Machine (SVM) for classification. …”
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers by Raja Mahmood, Raja Azlina, Abdi, AmirHossien, Hussin, Masnida

“…Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

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Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

“…Finally, the Buildings Footprint developed based on the algorithm was compared with the Buildings Footprint developed manually to assess the accuracy of the results. …”
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Investigation and analysis of crack detection using UAV and CNN: A case study of Hospital Raja Permaisuri Bainun by Goh, Wei Sheng, Wan Din, Wan Isni Sofiah, Waseem, Quadri, Zabidi, A.

“…Unmanned Aerial Vehicles (UAV) can automate, avoid visual inspection, and avoid other physical check-ups of these buildings. Automated crack detection using Machine Learning Algorithms (MLA), especially a Conventional Neural Network (CNN), along with an Unmanned Aerial Vehicle (UAV), can be effective and both can efficiently work together to detect the cracks in buildings using image processing techniques. …”
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Auditory Evoked Potentials (AEPs) Response Classification: A Fast Fourier Transform (FFT) and Support Vector Machine (SVM) Approach by Islam, Md Nahidul, Norizam, Sulaiman, Rashid, Mamunur, Mahfuzah, Mustafa, Md Jahid, Hasan

“…Then, the features have extracted with the help of Fast Fourier Transform (FFT), Power Spectral Density (PSD), Spectral Centroids, Standard Deviation algorithms. To classify the extracted features, the Support Vector Machine (SVM) approach using Radial Basis Kernel Function (RBF) has been used. …”
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