Search Results - (( based voting method algorithm ) OR ( java application learning algorithm ))
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…In a nut shell, we tried to introduce voting algorithms and structures suitable for large scale fault-tolerant systems which have optimal and proper time complexity (in parallel voting algorithms) and more reliability and availability (in enhanced m-out-of-n voting algorithm) compared to the basic types.…”
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Exact parallel plurality voting algorithm for totally ordered object space fault-tolerant systems
Published 2012“…To resolve the problem associated with sequential plurality voter in dealing with large number of inputs, this paper introduces a new generation of plurality voter based on parallel algorithms. Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. …”
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Stability of individual object in construction of voting-merged approach
Published 2019“…In this paper, we propose a voting-merged method - a combination of voting-based method and merging process. …”
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Dense-cluster based voting approach for license plate identification
Published 2018“…This paper presents a new method called Dense Cluster based Voting (DCV) for identifying an input license plate image as normal or taxi such that suitable recognition algorithms can be used to achieve better recognition rate. …”
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Ant system and weighted voting method for multiple classifier systems
Published 2018“…A diverse classifier ensemble is constructed by training them with different feature set partitions. The ant system-based algorithm is used to form the optimal feature set partitions. …”
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University Voting System Using Facial Recognition Technology
Published 2025conference output::conference proceedings::conference paper -
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh
Published 2019“…To bridge this gap, this research embarks on developing a hybrid machine learning approach to identify credit card fraud cases based on both benchmark and real-world data. Standard base machine learning algorithms, which include a total of twelve individual methods as well as the AdaBoost and Bagging methods, are firstly used. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
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Friendship Degree and Tenth Man Strategy: A new method for differentiating between erroneous readings and true events in wireless sensor networks
Published 2023“…The second stage will validate the voting process through a novel perspective based on the TMS. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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An improved multiple classifier combination scheme for pattern classification
Published 2015“…The most commonly used ensemble method is the random strategy while the majority voting technique is used as the combiner. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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A comparative study of the ensemble and base classifiers performance in Malay text categorization
Published 2017“…This paper intends to compare the effectiveness of ensemble with that of base classifiers for Malay text classification. Two feature selection methods (the Gini Index (GI) and Chi-square) with the ensemble methods are applied to examine Malay text classification, with the intention to efficiently integrate base classifiers algorithms into a more accurate classification procedure. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets
Published 2025“…Despite these varying results, all methods had a consensus for just 44 outliers. Employing ensemble techniques, both averaging and voting methods identified 155 outliers, whereas the weighted method highlighted 151, with a consensus of 150 outliers across the board. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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