Search Results - (( data visualisation learning algorithm ) OR ( evolution classification rules algorithm ))
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Experimental results demonstrated the compatibility of the proposed logical rule and the Discrete Hopfield Neural Network. Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Simultaneously, news sentiment analysis techniques were used to discover the polarity of news according to each factor. From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…Pandemics are highly unlikely events, therefore, we need a system to understand the statistics about the pandamic. Machine learning algorithms can analyse the data and then we can plan for handling the pandamic. …”
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…Pandemics are highly unlikely events, therefore, we need a system to understand the statistics about the pandamic. Machine learning algorithms can analyse the data and then we can plan for handling the pandamic. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Email spam classification based on deep learning methods: A review
Published 2025“…Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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The efficacy of personal computer (PC) AI image enhancer software on low and high contrast PA chest radiograph: an experimental study
Published 2026“…Conclusions: The findings highlight the effectiveness of AI software deep learning in visualising anatomical elements in CXR. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. …”
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Application of data mining techniques for economic evaluation of air pollution impact and control
Published 2007“…Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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Optimizing E-commerce inventory management using a machine-learning approach
Published 2025“…The results were visualised to generate actionable insights, enabling data-driven decisions. …”
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A survey of deep learning for lung disease detection on medical images: state-of-the-art, taxonomy, issues and future directions
Published 2020“…The taxonomy consists of seven attributes that are common in the surveyed articles: image types, features, data augmentation, types of deep learning algorithms, transfer learning, the ensemble of classifiers and types of lung diseases. …”
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Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Ultimately, the processed data has been visualised by using Matplot and stored via HBase. …”
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A collaborative filtering approach using machine learning and business intelligence: a critical review
Published 2025“…Specifically, we discovered that combining deep learning techniques with reinforcement learning algorithms enhanced recommendation reliability by 35% while improving user engagement measures by 25%. …”
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