Search Results - (( missing values system algorithm ) OR ( java application customization algorithm ))
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Detection Of Misplaced And Missing Regions In Image Using Neural Network
Published 2017“…Based on research, most of the algorithms are not intelligent enough and only able to detect the missing component. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Missing values in that attribute were replaced by the mode value. …”
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A novel approach for handling missing data to enhance network intrusion detection system
Published 2025“…Our approach employs the Random Missing Value (RMV) algorithm to simulate missing data, enabling thorough testing and comparison of various imputation techniques. …”
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Imputation Analysis of Time-Series Data Using a Random Forest Algorithm
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Solving nonlinear system of third-order boundary value problems using block method
Published 2014“…In this paper, we propose an algorithm of two-point block method to solve the nonlinear system of third-order boundary value problems directly. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…Then different features are derived from the segmented region using Gray Intensity Co-Occurrence Distribution Matrix (GICDM) which is processed by applying a proposed Supervised Jaya Optimized Rough Set based Feature Selection (SJORSFS) algorithm. These algorithms select the best features according to the fitness value, and its redundancy is to be reduced. …”
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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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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Boiler modeling and controller performance optimization using genetic algorithm for palm oil industry
Published 2020“…This research developed control algorithms and Graphical User Interfaces (GUI) using Genetic Algorithm (GA) optimization analysis for the boiler control system. …”
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NIS-Apriori-based rule generation with three-way decisions and its application system in SQL
Published 2020“…One of the topics that are considered is the possibility of estimating missing values via the obtained certain rules. The proposed methodology and the environment yielded by NIS-Apriori-based rule generation in SQL are useful for table data analysis with three-way decisions. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
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Wi-Fi signals database construction using chebyshev wavelets for indoor positioning systems
Published 2019“…The field tests as well as computer simulation results showed significant improvement in signal strength prediction accuracy compared to existing approximation algorithms. Furthermore, the proposed algorithm can recover missing signal values with much smaller number of on-site measurements compared to conventional calibration algorithm.…”
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An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The treatment of missing values and discretization are being carried out during the preprocessing stage. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. …”
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Faulty sensor detection using data correlation of multivariant sensor reading in smart agriculture with IOT
Published 2019“…In other cases. The system has a fault in a sensor when the correlation values between sensors are changed. …”
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