Search Results - (( using optimization based algorithm ) OR ( voting system based algorithm ))
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…All of these approaches attempt to generate diversity in the ensemble.However, classifier ensemble construction still remains a problem because there is no standard guideline in constructing a set of accurate and diverse classifiers. 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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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
Published 2018“…The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. …”
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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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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
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RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD
Published 2023“…This modeling is achieved using a Takagi-Sugeno (TS) fuzzy model and tuned by Gauss-Newton method for nonlinear regression (GNMNR) algorithm. …”
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A novel N-input voting algorithm for X-by-wire fault-tolerant systems
Published 2014“…In this paper, a novel voting algorithm is introduced for real-time fault-tolerant control systems, appropriate for applications in which N is large. …”
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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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Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.
Published 2010“…Therefore, this project intends to investigate the capability of multiple MLP system with majority voting technique. It is a system which consists of all the best-performed MLPs and a single final output from these MLPs is selected by the voting system. …”
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Research Reports -
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Secure E-Voting With Blind Signature
Published 2003“…We have developed an electronic voting system, E-Voting for a general election. E-Voting system employs cryptographic techniques to overcome the security issues in the election process. …”
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University Voting System Using Facial Recognition Technology
Published 2025conference output::conference proceedings::conference paper -
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Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile
“…It leverages the Synthetic Minority Over-sampling Technique (SMOTE) to address the class imbalance in the dataset and employs a Voting Ensemble with soft voting to combine several base algorithms (Logistic Regression, Random Forest, Gradient Boosting, and XGBoost/SVM) for accurate prediction of mental health levels (normal, mild, moderate, severe, very severe). …”
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Code-Based Signature Schemes For Online Voting System Based On The Blockchain Technology
Published 2022“…After the construction of these cryptographic primitives, we look into the possibility of implementations of these signature schemes for the online voting system based on the blockchain technology. …”
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Re-engineering grid-based quorum replication into binary vote assignment on cloud: A scalable approach for strong consistency in cloud databases
Published 2025“…This study proposes the Binary Vote Assignment in Cloud (BVAC), a cloud-native replication algorithm re-engineered from the Binary Vote Assignment on Grid Quorum (BVAGQ). …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
Published 2019“…Different machine learning algorithms (Artificial Neural Network [ANN], K Nearest Neighbor [KNN] and Support Vector Machine [SVM]) were tested individually and with various ensemble models (bagging, voting, and boosting) to detect the probability of the landslide and rockfall occurrences. …”
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Consensus algorithms blockchain: a comparative study
Published 2019“…In this research, we also presented a new category of the Blockchain consensus algorithms, which consist of three groups as follows; the proof based on Hardware, the proof based on stake, and the proof based on voting.…”
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An improved multiple classifier combination scheme for pattern classification
Published 2015“…In this study, an improved multiple classifier combination scheme is proposed. The ant system (AS) algorithm is used to partition feature set in developing feature subsets which represent the number of classifiers. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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