Search Results - (( developing constructing prediction algorithm ) OR ( java application using algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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Thesis -
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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Development Of Construction Noise Prediction Method Using Deep Learning Model
Published 2021“…A simple prediction chart method was developed on top of a stochastic algorithm called Monte Carlo simulation by complying with the standard BS 5228 for the noise prediction in the environmental impact assessment during the planning stage of a construction project. …”
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Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm
Published 2013“…To overcome such problem, a hybrid genetic algorithm-based Taguchi ANN (GA-Taguchi ANN) has been developed. …”
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Construction Noise Prediction Using Stochastic Deep Learning
Published 2022“…Lastly, the model is worthwhile to be further developed to fully exploit the potential of the stochastic deep learning noise prediction model in construction industries as a planning, managerial, and monitoring tool.…”
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Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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Delay and cost overrun of palm oil refinery construction projects: Artificial neural network (ann) model
Published 2021“…Artificial Bee Colony (ABC) algorithm was used to develop the prediction model for palm oil construction projects. …”
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Direct approach for mining association rules from structured XML data
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Thesis -
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Predicting customer churn in telecommunication service provider industry using Random Forest / Wan Muhammad Naqib Zafran Wan Roslan
Published 2023“…This project addresses the challenge of customer churn in the Telecommunications Service Provider (TSP) industry by focusing on the Random Forest algorithm for predictive modeling. This study aims to throughly explore the Random Forest algorithm, develop a robust Random Forest customer churn predictive model, and evaluate its performance in predicting customer churn within the internet service provider sector. …”
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Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao
Published 2024“…Traditional methods have been developed to predict overbreak. These predictions use either empirical-, statistical-, or numerical-based models. …”
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Thesis -
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Real-time algorithmic music composition application.
Published 2022“…This project is about the study of evolutionary music, and focuses on the development of an algorithmic music composer using the Java programming language. …”
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Final Year Project / Dissertation / Thesis -
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…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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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Final Year Project / Dissertation / Thesis -
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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A Conceptual Framework to Aid Attribute Selection in Machine Learning Student Performance Prediction Models
Published 2023“…The framework presents an opportunity to the researchers to pick constructive attributes for model development. We apply artificial neural network, a supervised learner, over a dataset to compare the performance of prediction models with distinct classes of attributes. …”
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