Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 10 of 10 for “"rule based algorithms"”.
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Intelligent and integrated load management system
… models and the decision support system using rule-based algorithms and expert systems. Each of these functions has shown the ability to produce more accurate results compared to classical techniques while at the same time requiring much less computing time and historical data. Development of …
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An Artificial Intelligence Based Approach to Automate Document Processing in Business Area
… model outperforms the other commonly used rule-based algorithms, RIPPER and PART, showing that the proposed model is potentially suitable to be deployed into business to classify the documents.
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Context Aware Textual Entailment
… participants to make assumptions (hypothesis) based on background knowledge, a process called entailment. These assumptions may then be supported, contradicted, or refined as a conversation or story progresses and additional facts become known and context changes. It is often the case that we …
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Epileptic Seizure Detection And Prediction From Electroencephalogram Using Neuro-Fuzzy Algorithms
… dissertation presents innovative approaches based on fuzzy logic in epileptic seizure detection and prediction from Electroencephalogram (EEG). The fuzzy rule-based algorithms were developed with the aim to improve quality of life of epilepsy patients by utilizing intelligent methods. An …
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The effectiveness of automatic item generation for the development of cognitive ability tests
… has shown that the increased use of computer-based testing has brought about new challenges. With the ease of online test administration, a large number of items are necessary to maintain the item bank and minimise the exposure rate. However, the traditional item development process is …
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Deriving Classifiers with Single and Multi-Label Rules using New Associative Classification Methods
… Classification (AC) in data mining is a rule based approach that uses association rule techniques to construct accurate classification systems (classifiers). The majority of existing AC algorithms extract one class per rule and ignore other class labels even when they have large data …
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Applying Rotation-Equivariant Deep Learning to Cloud and Road Segmentation in Satellite and Aerial Imagery
… Many existing state-of-the-art cloud detection algorithms require multispectral inputs and sometimes confuse clouds with snow, ice, or cold water. We propose deep learning models trained on visible-spectrum, long-wave infrared (LWIR), and short-wave infrared (SWIR) imagery for on-orbit cloud …
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AI-DRIVEN ATRIAL ARRHYTHMIA DETECTION: DEVELOPMENT, CROSS-COMPARISON AND UNCERTAINTY QUANTIFICATION OF ALGORITHMS FOR CLINICAL CONTINUOUS ECGS
… Traditional detection methods, primarily based on electrocardiograms (ECGs) analyzed by clinicians, are often time-consuming and prone to human error, especially when dealing with long-term monitoring (Holter recordings) and subtle, intermittent atrial arrhythmias. Recently, the …
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Intelligent network intrusion detection using an evolutionary computation approach
… into two major categories of signature-based and anomaly-based. A signature-based IDS stores the signature of known attacks in a database and discovers occurrences of attacks by monitoring and comparing each communication in the network against the database of signatures. On the other …
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Advancing precision medicine: harnessing data from diverse sources and individuals to predict medication efficacy and safety.
… populations, as they often receive treatments based on population averages, which can result in inefficacy or increased prevalence of side effects. Throughout this research, I became aware of the gap in high-quality data for underserved populations, primarily due to their limited participation …