Search Results - (( development programme learning algorithm ) OR ( java classification model algorithm ))

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). However, the process failed to state clearly the encoding strategy in its initial stage. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

“…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

“…It consists of 3-stage procedures: feature ranking, feature selection and classification. Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
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Prioritisation Assessment and Robust Predictive System for Medical Equipment: A Comprehensive Strategic Maintenance Management by Aizat Hilmi Zamzam, Ayman Khallel Ibrahim Al-Ani, Ahmad Khairi Abdul Wahab, Khin Wee Lai, Suresh Chandra Satapathy, Azira Khalil, Khairunnisa Hasikin, Muhammad Mokhzaini Azizan

Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…Generally, these source codes go through the preprocessing, comparison, extraction, generate program semantics and classification processes. A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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Predicting usage for a marketable e-learning portal by Yaacob, Aizan, Yusof, Yuhanis, Sheik Osman, Wan Rozaini, Derashid, Chek, Omar Khan, Zainizad

“…To date, existing e-learning portals focuses on providing various learning materials via online.Such an approach may provide huge benefit to the learners; nevertheless, less value can be obtained by the developers or owners.The knowledge transfer programme provides an insight on how existing e-learning portal can be upgraded.The academia has introduced the industry to a computational modelling that is built upon the behaviour of nature community (i.e bees)The utilization of Artificial Bee Colony algorithm in predicting learners' usage of an e-learning portal provides an indicator to the developers on the portals effectiveness.Such information is then useful in producing a marketable and valuable e-learning portal…”
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Prediction of MUET result based on KNN algorithm / Siti Fatimah Azzahra Hamrizan by Hamrizan, Siti Fatimah Azzahra

“…The machine learning technique used to develop the prediction prototype is the KNN algorithm. …”
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A Machine Learning Classification Application to Identify Inefficient Novice Programmers by Khan I., Al-Mamari A., Al-Abdulsalam B., Al-Abdulsalam F., Al-Khansuri M., Iqbal Malik S., Ahmad A.R.

A step towards the development of VHDL model for ANN based EMG signal classifier by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…A feed-forward ANN with back-propagation learning algorithm is used for the classification of EMG signals. …”
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Computerised Heuristic Algorithm for Multi-location Lecture Timetabling by Kuan, Huiggy

“…A two-stage heuristic algorithm is proposed to solve the multi-location timetabling problem on MSc HRD coursework programme. …”
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Enhancing problem-solving skills of novice programmers in an introductory programming course by Malik S.I., Mathew R., Al-Sideiri A., Jabbar J., Al-Nuaimi R., Tawafak R.M.

CT-eKit: computational thinking interactive learning / Ong Sing Ling, Jill Ling and Fetylyana Nor Pazilah by Ong, Sing Ling, Jill, Ling, Pazilah, Fetylyana Nor

“…Hence, this innovation aims to innovate a CTeKit, a collective teaching aid that emphasises Inquiry-based learning (IBL), developed to facilitate the learning process on the CT topic. …”
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A flowchart-based multi-agent system for assisting novice programmers with problem solving activities by Hooshyar D., Ahmad R.B., Raj R.G., Nizam M.H.N.M., Yousefi M., Horng S.-J., Rugelj J.

Examination timetabling for undergraduate programme using graph coloring approach / Norarida Abd Rhani ... [et al.] by Abd Rhani, Norarida, Mat Saad, Nor Najihah, Zulkfeli, Nabilah, Mazlan, Mardhiyah Marisha, Mahmud, Maziah, Mohamad, Siti Nurul Fitriah, Wan Yusoff, Wan Roslini

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Trap colour strongly affects the ability of deep learning models to recognize insect species in images of sticky traps by Song-Quan Ong, Toke Thomas Høye

“…CONCLUSION: Our results support the development of an automatic classification of pests on a sticky trap, which should focus on colour and deep learning architecture to achieve good results. …”
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