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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Combinations of feature selection and classification algorithms were used for mortality prediction post ACS. …”
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A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…This simple model-free butterfly shape-based detection (BSD) method uses Stenman's one parameter stiction model, which results in a distinctive â��butterflyâ�� pattern in the presence of stiction. …”
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Extraction and Optimization of Fuzzy Protein Sequences Classification Rules Using GRBF Neural Networks
Published 2003“…Traditionally, two protein sequences are classified into the same class if their feature patterns have high homology. These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
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Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network
Published 2007“…It will be also an ideal case when dealing with ECG signals where the pattern of signals varies as it depends on the condition of patience at very short frame of time.In this paper the recursive learning algorithms is being tested on an Augmented a Multilayer- Perceptron (MLP) or also known as Direct-Link MLP (DMLP) networks. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. Machine learning algorithms are capable of learning linear and nonlinear patterns in complex agro-meteorological data. …”
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An algorithm for Elliott Waves pattern detection
Published 2018“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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An algorithm for Elliott Waves pattern detection
Published 2018“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Subjects:Conference paper -
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Financial time series predicting using machine learning algorithms
Published 2013“…Finding of research papers, the financial trend patterns repeat itself in the history. Thus, this research motivates and aims to investigate the repeat behaviour and pattern of trends from the historical financial time series data, and utilise the strength of machine learning techniques to develop a promising financial time series predictor engine. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm
Published 2023“…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”
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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…The algorithms are ACS(GA), ACS+GA, ACS(TS), and ACS+TS. …”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition
Published 2010“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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The application of voltage sags pattern to locate a faulted section in distribution network
Published 2010“…A pattern matching approach between simulated voltage sag and measurement is proposed to identify the faulted section. …”
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Advanced flood prediction at forest with rainfall data using various machine learning algorithms
Published 2024“…The aim is to classify and predict floods in advance with rain data patterns of India using spatio-temporal logic. Two Classification algorithms are used to achieve the maximum accuracy namely K-Nearest Neighbour with a sample size=5 and Logistic Regression with a sample size=5 for continues iterations. …”
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