Search Results - (( based voting method algorithm ) OR ( using optimization method algorithm ))

Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…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 and weighted voting method for multiple classifier systems by Husin, Abdullah, Ku-Mahamud, Ku Ruhana

“…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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Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…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 by Haniff, Mohamad Fadzli, Selamat, Hazlina, Khamis, Nuraqilla, Alimin, Ahmad Jais

“…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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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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An ensemble method with cost function on churn prediction by Mohd Khalid, Awang, Mohammad Afendee, Mohamed, Mokhairi, Makhtar

“…The combination of ensemble classifier is calculated based on the simple majority voting algorithm. The performance measure used in determining the optimal subset of classifiers is the combination of Accuracy (ACC), True Negative Rate (TNR) and True Positive Rate (TPR). …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

“…Grid search method was adopted to optimise the hyperparameters of the investigated base models. …”
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RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD by Homod R.Z., Mohamed Sahari K.S., Almurib H.A.F., Nagi F.H.

“…This modeling is achieved using a Takagi-Sugeno (TS) fuzzy model and tuned by Gauss-Newton method for nonlinear regression (GNMNR) algorithm. …”

Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings by Homod R.Z., Gaeid K.S., Dawood S.M., Hatami A., Sahari K.S.

Accurate and reliable diagnosis and classification using probabilistic ensemble simplified fuzzy ARTMAP by Loo, C.K., Rao, M.V.C.

“…In this paper, an accurate and effective probabilistic plurality voting method to combine outputs from multiple simplified fuzzy ARTMAP (SFAM) classifiers is presented. …”
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Exact parallel plurality voting algorithm for totally ordered object space fault-tolerant systems by Karimi, Abbas, Zarafshan, Faraneh, Jantan, Adznan, Ramli, Abdul Rahman, Saripan, M. Iqbal, Syed Mohamed, Syed Abdul Rahman Al-Haddad

“…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 by Shamsuddin, Norin Rahayu, Mahat, Nor Idayu

“…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 by Asadzadehkaljahi, Maryam, Shivakumara, Palaiahnakote, Roy, Sangheeta, Olatunde, Mojeed Salmon, Anisi, Mohammad Hossein, Lu, Tong, Pal, Umapada

“…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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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS by Fanos, Ali Mutar

“…The proposed BANN model achieved the best training accuracies of (95%) and best prediction accuracies of (92%) based on testing data compared to other employed methods. …”
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University Voting System Using Facial Recognition Technology by Nur Amni Fatini Mohd Nain, Farida Hazwani Mohd Ridzuan, YS Yusoff

A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…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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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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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 by Adday, Ghaihab Hassan, Subramaniam, Shamala K., Zukarnain, Zuriati Ahmad, Samian, Normalia

“…The second stage will validate the voting process through a novel perspective based on the TMS. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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