Search Results - (( missing data prediction algorithm ) OR ( java simulation optimization 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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PREDICTION MODEL OF MISSING DATA: A CASE STUDY OF PM10 ACROSS MALAYSIA REGION
Published 2018“…Imputation methods of EMB-algorithm and nearest neighbor were applied to treat missing data before analyzed by Fit model, MLR and ANN. …”
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Data prediction and recalculation of missing data in soft set / Muhammad Sadiq Khan
Published 2018“…Soft sets with incomplete data cannot be used in applications. Few researchers have worked on data filling and recalculating incomplete soft sets, and the current research focuses on predicting missing values and decision values from non-missing data or aggregates. …”
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5
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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Proceeding Paper -
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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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An Evaluation of Machine Learning Algorithms for Missing Values Imputation
Published 2019“…Our research paper presents a review of missing values imputation approaches. It represents the research and imputation of missing values in gene expression data. …”
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MISSING DAILY RAINFALL PREDICTION USING GREY WOLF OPTIMIZER-BASED NEURAL NETWORK
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Book Chapter -
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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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Book Chapter -
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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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Neural Network with Genetic Algorithm Prediction Model of Energy Consumption for Billing Integrity in Gas Pipeline
Published 2012“…In this paper, several techniques will be discuss and selected including neural network prediction model, least square vector regression and combination of either two methods mentioned before with genetic algorithm as preferable technique to indicate the missing data. …”
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Final Year Project -
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SINE COSINE ALGORITHM BASED NEURAL NETWORK FOR RAINFALL DATA IMPUTATION
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Book Chapter -
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DEVELOPMENT OF MULTI-VERSE OPTIMIZER IN ARTIFICIAL NEURAL NETWORK FOR ENHANCING THE IMPUTATION ACCURACY OF DAILY RAINFALL OBSERVATIONS
Published 2024“…While MVOFNN did not outperform the others in imputation performance, it showcased robustness, reliability, and feasibility in predicting missing daily rainfall data.…”
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Book Chapter -
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An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
Published 2023Conference Paper -
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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid
Published 2022“…The methodology includes drive test measurement for data collection, exploratory data analysis, data preparation, and applying machine learning algorithms to predict mobile network performance. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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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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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Comparative analysis of imputation methods for enhancing predictive accuracy in data models
Published 2024“…The presence of missing values within datasets can introduce a detrimental bias, significantly impeding the predictive algorithm's ability to discern patterns and accurately execute prediction. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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