Search Results - parallel process ((mining algorithm) OR (learning algorithm))*
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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Prognosis of early cervical carcinoma using gene expression profiling
Published 2015“…Our results indicate that gene expression profiles combined with carefully chosen learning algorithms can predict patient survival for certain diseases.…”
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Parallel execution of distributed SVM using MPI (CoDLib)
Published 2023“…To reduce the computational time during the process of training the SVM, a combination of distributed and parallel computing method, CoDLib have been proposed. …”
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Fast and efficient sequential learning algorithms using direct-link RBF networks
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Parallel backpropagation neural network training for face recognition
Published 2023“…In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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A spark-based parallel fuzzy C median algorithm for web log big data
Published 2022“…Based on the Rand Index and SSE (sum of squared error), the parallel Fuzzy C median algorithm's performance is evaluated in the PySpark platform. …”
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A novel association rule mining approach using TID intermediate itemset
Published 2018“…Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. …”
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A novel association rule mining approach using TID intermediate itemset
Published 2018“…Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. …”
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Optimizing OLAP heterogeneous computing based on Rabin-Karp algorithm
Published 2013“…Yet, such a method will always need increasing processing resources. Numerous enhancements have been suggested in order to improve OLAP performance, part of them has gone to the processing capabilities whereby parallel processing has occupied a sizeable space. …”
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Proceeding Paper -
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…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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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…In this paper, a parallel deep learning-based community detection method in large complex networks (CNs) is proposed. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…Composed of three levels of learning, the proposed ensemble model employs two base learners and a meta-learner, and is executed in parallel processing platform to achieve efficient computation. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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Leveraging data lake architecture for predicting academic student performance
Published 2024“…With its parallel processing capabilities, this centralized data repository facilitates the training and evaluation of various machine learning models for prediction. …”
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Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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