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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2015“…The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. …”
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Investigation of features for classification RFID reading between two RFID reader in various support vector machine kernel function
Published 2022“…An indoor positioning using RFID technology based on various kernel function of the support vector machine (SVM), and feature extraction are proposed to determine the location of the goods. …”
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Conference or Workshop Item -
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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The capabilities of Multiclass Support Vector Machine (MSVM) training algorithms in grading agarwood essential oil
Published 2024“…The MSVM was constructed utilizing radial bias function as the kernel function using MATLAB2021b. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…In this research, the LDA gives as higher as 85.8% of accuracy with six units of the sensors used compared to SVM which is 85% of accuracy percentage with five units of the sensors used. …”
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
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Comparative performance of machine learning algorithms for cryptocurrency forecasting
Published 2018“…Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. …”
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A fuzzy approach for early human action detection / Ekta Vats
Published 2016“…It combines the benefits of computer vision and fuzzy set theory based on fuzzy BK subproduct. The novelty lies in the construction of a frame-by-frame membership function for each kind of possible movement, taking into account several human actions from a publicly available dataset. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…LC-RF is tested with other base classifiers such as k-NN, SVM and HMM. However, LC-RF showed the most promising results among others. …”
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Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…The effectiveness of this algorithm is investigated by comparing with other AC based feature extraction algorithms involving AC/LDA (Linear Discriminant Analysis) and AC/PCA (Principal Component Analysis). …”
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GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators
Published 2024“…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2021“…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2021“…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2022“…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2022“…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review
Published 2022“…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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