Search Results - (( develop missing data algorithm ) OR ( java application using algorithmic ))
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Missing tags detection algorithm for radio frequency identification (RFID) data stream
Published 2019“…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
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Missing-values imputation algorithms for microarray gene expression data
Published 2019“…The aim was to adapt the algorithms to the characteristics of the data.…”
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Book Chapter -
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An Evaluation of Machine Learning Algorithms for Missing Values Imputation
Published 2019“…It represents the research and imputation of missing values in gene expression data. By using the local or global correlation of the data we focus mostly on the contrast of the algorithms. …”
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Development of an imputation technique - INI for software metric database with incomplete data
Published 2007“…Missing data causes significant problem. With inaccurate data or missing data, it is very difficult to know how much a project will cost or worth. …”
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Book Section -
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Enhanced mechanism to handle missing data of Hadith classifier
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Proceeding Paper -
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Article -
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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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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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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Missing values lead to the difficulty of extracting useful information from that data set. …”
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10
MISSING DAILY RAINFALL PREDICTION USING GREY WOLF OPTIMIZER-BASED NEURAL NETWORK
Published 2024“…Comparative analyses were conducted against the Levenberg-Marquardt Feedforward Neural Network (LMFNN) and the K-Nearest Neighbour (KNN) algorithm, both of which are recognized for their reliability in addressing missing rainfall data. …”
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Book Chapter -
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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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Neural Network with Genetic Algorithm Prediction Model of Energy Consumption for Billing Integrity in Gas Pipeline
Published 2012“…Along the development of oil and gas industry, missing data is one of the contributors that restrains in analyzing and processing data task in database. …”
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Final Year Project -
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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…Missing data is a widespread data quality issue across various domains. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…Missing data is a widespread data quality issue across various domains. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…When there are missing data in the dataset, TSP may use TSE for estimation of missing data and then performs prediction. …”
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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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Stroke-to-stroke matching in on-line signature verification
Published 2010“…This project suggesting a modified DTW algorithm with the proposed Missed Nodes Recovery Algorithm aims to improve the mapping performance, hence the development of stroke to stroke signature comparison is possible. …”
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Thesis