Search Results - (( java implementation learning algorithm ) OR ( some selection process algorithm ))

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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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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Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa by Mustapa, Nor Aishah

“…Diabetes Prediction system using clonal selection algorithm is available to test whether patients suffering from diabetes or not. …”
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Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles by Ihsan, Afdhalul, Rainarli, Ednawati

“…The way to solve this problem is to conduct the feature selection process. There are several filter-based feature selection methods; some are Chi-Square, Information Gain, Genetic Algorithm, and Particle Swarm Optimization (PSO). …”
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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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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences by Rajesvary Rajoo R., Salam R.A.

Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

“…The TF-IDF algorithm is used to filter Android features filtered before detection process. …”
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Evaluation of feature selection algorithm for android malware detection by Mazlan, Nurul Hidayah, A Hamid, Isredza Rahmi

“…The Android features were filtered before detection process using TF-IDF algorithm. However, IDF is unaware to the training class labels and give incorrect weight value to some features. …”
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Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

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VHDL modeling of optimum measurement selection by using genetic algorithm by Ullah, Mohammad Habib, Hasan, Muhammad Asfarul, Uddin, Md. Jasim, Priantoro, Akhmad Unggul

“…A Genetic Algorithm (GA) that is going to be a part of a system for obtaining optimum sensor measurements for a specific process. …”
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Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

“…There will be two processes involved, which are feature extraction using minutiae-based method and also the implementation of the proposed algorithm, CSA. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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A Comparative Study Of Blockchain Algorithms For Non-Fungible Token by Woo, Jan Yin

“…In this research, there will be some selected algorithms, which is Proof-of-Work and Proof-of-Stakes from open resource and modified to the suitable testing criteria to evaluate valid and sufficient data for data visualization. …”
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A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

“…Results obtained showed that the proposed algorithm outperforms some of the existing techniques. …”
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Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm by Zeni, Saltihie

“…Then, the modified LEACH algorithm was proposed where the improvement was done in cluster head selection based on LEACH. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Self organizing multi-objective optimization problem by Ismail, Fatimah Sham, Yusof, Rubiyah, Khalid, Marzuki

“…However, this approach has some limitations because of the difficulty in selecting an appropriate weight for each objective and the need of some knowledge about the problems. …”
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