Search Results - (( developing learning risk algorithm ) OR ( java visualization using algorithm ))

A performance analysis of association rule mining algorithms by Fageeri, S.O., Ahmad, R., Alhussian, H.

“…In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. …”
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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

“…An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin by Nasaruddin, Amir Hambaly

“…D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

“…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

“…Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. …”
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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

“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

“…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”

Dynamic force-directed graph with weighted nodes for scholar network visualization by Mohd. Aris, Khalid Al-Walid, Ramasamy, Chitra, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023 by Soomro, Anam, Zakariyah, Habeebullah, Aftab, S.M.A., Muflehi, Mohamad, Shah, Asadullah, Meraj, Syeda

“…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. It critically examines the transition from traditional statistical models to advanced ML techniques in assessing credit risk, with a focus on the banking sector's need for reliable default prediction methods. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. Aiming at the characteristics of unbalanced loan data and high noise, this paper proposes an improved Gray Wolf optimization strategy (PSOEBGWO). …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

“…The development of Management Information Systems (MIS) is impossible without the use of machine learning (ML). …”
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Detection of Fraud and Non-Fraud Transaction using Machine Learning Algorithm by Sujang Karing, Darryl

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Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

“…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. …”
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Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables by Che Dom, Nazri, Mohd Hardy Abdullah, Nur Athen, Dapari, Rahmat, Salleh, Siti Aekbal

“…Integrating time-lagged microclimatic variables into machine learning frameworks enhances the predictive accuracy of dengue risk indicators at a fine spatial scale. …”
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Towards development of robust machine learning model for Malaysian corporation: a systematic review of essential aspects for corporate credit risk assessment / Zulkifli Halim and S... by Halim, Zulkifli, Mohamed Shuhidan, Shuhaida

“…This study is an overview of the development of robust machine learning for Malaysian corporation credit risk assessment. …”
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Using machine learning algorithms to develop a clinical 2 decision-making tool for COVID-19 inpatients by Vepa, Abhinav, Saleem, Amer, Rakhshan, Kambiz, Daneshkhah, Alireza

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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

“…The results demonstrate that the machine learning-based approach achieved high predictive accuracy in identifying individuals at risk of stroke. …”
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A review on supervised machine learning for accident risk analysis: challenges in Malaysia by Choo, Boon Chong, Abdul Razak, Musab, Awang Biak, Dayang Radiah, Mohd Tohir, Mohd Zahirasri, Syafiie, S.

“…This review observed how the IR 4.0 approaches were used in the risk analysis, especially on supervised machine learning. …”
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