Search Results - (( java implementation path algorithm ) OR ( missing value using algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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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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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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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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Missing-values imputation algorithms for microarray gene expression data
Published 2019“…Numerous bioinformatics examination tools are used for cancer prediction, including the data set matrix (Bailey et al., Cell 173(2):371–385, 2018); thus, it is necessary to resolve the problem of missing-values imputation. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data
Published 2021“…K-nearest neighbors (KNN) has been extensively used as imputation algorithm to substitute missing data with plausible values. …”
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Systematic review on missing data imputation techniques with machine learning algorithms for healthcare
Published 2022“…Many machine learning algorithms have been applied to impute missing data with plausible values. …”
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Detection Of Misplaced And Missing Regions In Image Using Neural Network
Published 2017“…The neural network uses the RGB value from the image processing phase and analyzes the regions to check whether there is misplaced or missing jigsaw puzzle. …”
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Improving knowledge extraction of Hadith classifier using decision tree algorithm
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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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ExtraImpute: a novel machine learning method for missing data imputation
Published 2022“…This approach imputes each missing value that exists in features by predicting its value using other observed values in the dataset. …”
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Enhanced mechanism to handle missing data of Hadith classifier
Published 2011“…Decision tree algorithms have the ability to deal with missing values or wrong data. …”
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Missing values imputation tool using imputex algorithm
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Missing value estimation methods for data in linear functional relationship model
Published 2017“…Missing value problem is common when analysing quantitative data. …”
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Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data
Published 2024“…The complexity of compositional data with missing values renders traditional estimation methods inadequate. …”
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SINE COSINE ALGORITHM BASED NEURAL NETWORK FOR RAINFALL DATA IMPUTATION
Published 2024“…This chapter presents the ability of the sine cosine algorithm-based neural network (SCANN) to predict and optimize missing rainfall at different percentages of missing rates. …”
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