Search Results - (( parallel classification new algorithm ) OR ( using codification using algorithm ))

Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. …”
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Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach by Ab. Malik, Rosely, Jamil S., Mohamed

“…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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Adaptive resource allocation for reliable performance in heterogeneous distributed systems. by Hussin, Masnida, Abdullah, Azizol, K. Subramaniam, Shamala

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Square patch feature based face detection architecture for high resolution smart camera by Mohd Mustafah, Yasir, Bigdeli, Abbas, Azman, Amelia Wong, Lovell, Brian

“…In this paper, we proposed a face detection architecture that is suitable to be implemented on a smart camera system. The face detection algorithm is based on a new weak classifier type that we called square patch feature. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…This research proposes a new enhancement technique based on the Adaptive Histogram Equalization (AHE) method. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…This research proposes a new enhancement technique based on the Adaptive Histogram Equalization (AHE) method. …”
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Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani by Mirhassani, Seyedmostafa

“…In case of multiple filterbanks the cepstral features are used in different experts for performing classification based on different representation of speeches. …”
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