Search Results - (( development missing learning algorithm ) OR ( java application testing algorithm ))
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Thesis -
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
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Article -
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Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm
Published 2021“…In this work, preliminary study of the implementation of one of the latest deep learning algorithms, i.e. YOLOv5, has been carried out in the detection and classification of missing road lane markings. …”
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Proceeding Paper -
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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Imputation Analysis of Time-Series Data Using a Random Forest Algorithm
Published 2024“…Missing data poses a significant challenge in extensive datasets, particularly those containing time-series information, leading to potential inaccuracies in data analysis and machine learning model development. …”
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Conference or Workshop Item -
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa
Published 2020“…The results demonstrate that the performance measure of 90.77% has been recorded for detection rate with average processing time of 1.02 to 1.04 seconds per image. The developed algorithm is reported to be reliable to assist the radiologist in ischemic PF diagnosis which is important for future healthcare needs.…”
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Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network
Published 2006“…The back propagation algorithm was adopted for this study. The optimal model for predicting missing data found in this study is the network with the combination of learning rate and the number of neurons in the hidden layer of 0.2 and 60. …”
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Final Year Project Report / IMRAD -
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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Undergraduates Project Papers -
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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours
Published 2010“…An enhanced Bucket Brigade Algorithm (BBA) is developed to avoid the problem of choosing classifiers with high strength value but with incorrect behaviour. …”
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Federated deep learning for automated detection of diabetic retinopathy
Published 2022“…Federated learning allows deep learning algorithms to learn from a diverse set of data stored in multiple databases. …”
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Proceeding Paper -
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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