Search Results - (( java implementation learning algorithm ) OR ( knowledge solution means 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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
Get full text
Get full text

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. …”
Get full text
Get full text

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…In addition, it is considered that existing solutions do not provide a feature driftaware solution to the concept drift adaptable solution, which exploits the fact that many of the original features are non-relevant. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Tacit knowledge for business intelligence framework using cognitive-based approach by Surbakti, Herison

“…Tacit knowledge becoming a key issue in business intelligence approach to knowledge systems. …”
Get full text
Get full text

Fuzzy genetic algorithms for combinatorial optimisation problems by Varnamkhasti, Mohammad Jalali

“…Fuzzy Logic Controllers (FLCs) are considered as knowledge-based systems, incorporating human knowledge. …”
Get full text
Get full text

Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
Get full text
Get full text
Get full text

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

Get full text
Get full text
Get full text

Average concept of crossover operator in real coded genetic algorithm by Abd Rahman, Rosshairy, Ramli, Razamin

“…As the most important search operator in a Genetic Algorithm (GA) approach, many procedures have been proposed to accomplish the idea of a crossover.As a result, knowledge in crossover has incorporated special features such as statistical elements (i.e. arithmetic crossover) and natural observation (i.e. queen bee crossover) to name a few.Thus, this paper proposed a mean or average concept of crossover for finer parents to produce a new offspring in a GA based approach in an animal diet formulation problem.Experiments using real data were carried out involving GA models with average crossover and one-point crossover.Subsequently, the incorporation of power heuristics as a repair operator was investigated to find the best combination of ingredients, while removing the unwanted ones.Comparisons were made between GA models incorporating repair operator with different crossovers: average crossover and one point crossover.The results show that the performance of average crossover is comparable with that of the one point crossover.The inclusion of the repair operator provides an advantage that shows interesting solution for the tested problem.…”
Get full text
Get full text
Get full text

The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning by Noor, Ubair, Hassan, Raini, Dwi Handayani, Dini Oktarina

“…The preliminary results using the K means Clustering Algorithm showed that the conceptual framework successfully grouped similar data points, facilitating the identification of skyline points. …”
Get full text
Get full text
Get full text
Get full text

Solving New Student Allocation Problem (NSAP) with Analytical Hierarchy Process (AHP) by Wan Hussin, Wan Haniza, Shibghatullah, Abdul Samad, Shahbodin, Faaizah

“…The problem is the students are allocated to their class randomly, just by using their registration number and by all means without referring to their intelligence level, knowledge, skills and also their performance. …”
Get full text
Get full text

A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
Get full text
Get full text
Get full text

Solving New Student Allocation Problem (NSAP) With Analytical Hierarchy Process (AHP) by Shahbodin, Faaizah, Wan Hassim, Wan Haniza, Shibghatullah, Abdul Samad

“…There are many approaches used to solve New Student Allocation Problem (NSAP).Many researchers use application of Genetic Algorithm (GA).However,the study presented in this paper applies an Analytical Hierarchy Process (AHP)technique in solving New Student Allocation Problem (NSAP) handled by Registration Unit at Ungku Omar Polytechnic.The problem is the students are allocated to their class randomly,just by using their registration number and by all means without referring to their intelligence level,knowledge,skills and also their performance.So,in this paper the researcher’s focus is on solving NSAP by using AHP to allocate students into their respective classes with minimum intelligence gap in each class and the number of students in each class does not exceed its maximum capacity.The proposed solution will be tested using real data from the Politeknik Ungku Omar to see the result. …”
Get full text
Get full text
Get full text
Get full text

Data stream clustering by divide and conquer approach based on vector model by Khalilian, Madjid, Mustapha, Norwati, Sulaiman, Nasir

“…The continuous effort on data stream clustering method has one common goal which is to achieve an accurate clustering algorithm. However, there are some issues that are overlooked by the previous works in proposing data stream clustering solutions; (1) clustering dataset including big segments of repetitive data, (2) monitoring clustering structure for ordinal data streams and (3) determining important parameters such as k number of exact clusters in stream of data. …”
Get full text
Get full text

End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

“…The Normalized Mean Square Error (NMSE) and the BER perfor�mances for different DVB-S2X system MODCODs are investigated and the results for these algorithms are compared with the conventional Minimum Mean Square Er�ror (MMSE) and Least Square (LS) channel estimation techniques. …”
Get full text
Get full text