Search Results - (( based voting method algorithm ) OR ( evolution optimization mining algorithm ))

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

“…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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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

“…During the retrieval phase, a new activation function and Swarm Mutation were proposed to ensure the diversity of the neuron states. The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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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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Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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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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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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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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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

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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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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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An improved multiple classifier combination scheme for pattern classification by Abdullah,

“…The most commonly used ensemble method is the random strategy while the majority voting technique is used as the combiner. …”
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A comparative study of the ensemble and base classifiers performance in Malay text categorization by Alshalabi, Hamood Ali, Sabrina Tiun, Nazlia Omar

“…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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Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets by Abri K.Al., Sidhu M.S.

“…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. …”

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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Data mining reduction methods and performances of rules by Ahmad, Faudziah, Basir, Mohammad Aizat

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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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