Search Results - (( java implementation path algorithm ) OR ( based missing _ 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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2
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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3
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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4
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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5
Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment
Published 2016“…Based on the analysis, the proposed singular imputation algorithms, which treated missing data by geometric means, harmonic means and medians are more superior compared to the other imputation algorithms, irrespective of missing rates and rainfall stations. …”
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6
Determination of the best single imputation algorithm for missing rainfall data treatment
Published 2016“…Based on the analysis, the proposed singular imputation algorithms, which treated missing data by geometric means, harmonic means and medians are more superior compared to the other imputation algorithms, irrespective of missing rates and rainfall stations.…”
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7
Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…Models were tested with both complete and missing output data to evaluate the robustness of the IAOA-based method. …”
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8
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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Restoration of missing data in old archives based on genetic algorithm
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10
MISSING DAILY RAINFALL PREDICTION USING GREY WOLF OPTIMIZER-BASED NEURAL NETWORK
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11
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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12
An Evaluation of Machine Learning Algorithms for Missing Values Imputation
Published 2019“…We considered the algorithms in a global, hybrid, local, and knowledge-based technique. …”
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The Effectiveness Of A Probabilistic Principal Component Analysis Model And Expectation Maximisation Algorithm In Treating Missing Daily Rainfall Data
Published 2020“…The proposed imputation algorithms are based on the M-component probabilistic principal component analysis model and an expectation maximisation algorithm (MPPCA-EM). …”
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14
Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…The novel optimization-based artificial intelligence algorithm proposed in this paper implies an improved way to overcome a real engineering challenge i.e. handling missing values for better RUL prediction, hence bringing great opportunities for the domain area. …”
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15
An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data
Published 2021“…Thus, this paper proposes a novel method for imputation of missing data, named KNNGOA, which optimized the KNN imputation technique based on the grasshopper optimization algorithm. …”
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16
The effectiveness of a probabilistic principal component analysis model and expectation maximisation algorithm in treating missing daily rainfall data
Published 2020“…The proposed imputation algorithms are based on the M-component probabilistic principal component analysis model and an expectation maximisation algorithm (MPPCA-EM). …”
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17
Missing-values imputation algorithms for microarray gene expression data
Published 2019“…By using local and global correlation of the data, we were able to focus mostly on the differences between the algorithms. We classified the algorithms as global, hybrid, local, or knowledge-based techniques. …”
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18
Detection Of Misplaced And Missing Regions In Image Using Neural Network
Published 2017“…Therefore, it is necessary to develop an algorithm that is able to detect both misplaced and missing jigsaw puzzles. …”
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19
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Classification rules were generated based on the best reduct. For the problem of missing data, a new approach was proposed based on data partitioning and function mode. …”
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20
Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm
Published 2020“…The missing data is imputed by using both NNM and EM algorithm. …”
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