Search Results - (( intelligence valid learning algorithm ) OR ( intelligence based data algorithm ))*
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Hybrid Intelligent Warning System for Boiler tube Leak Trips
Published 2017“…The first intelligent warning system (IWS-1) represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2) represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…Many fields such as data science, data mining suffered from the rapid growth of data volume and high data dimensionality. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…This research proposes a low-cost alternative using intelligent fruit selection systems based on computer vision techniques to address these issues. …”
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Bot detection using machine learning algorithms on social media platforms
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Automated cone cut error detection of bitewing images using convolutional neural network
Published 2023“…Introduction: Cone cut error is one of the technical errors that can hinder the important information from a bitewing radiograph. Meanwhile, deep learning is a specialized artificial intelligence method where an algorithm can be trained to automatically detect, classify and give output based on the trained dataset. …”
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Proceeding Paper -
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Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction
Published 2022“…Then, the natural language processing (NLP) algorithm was applied to the unique data column and extracted a huge number of useful data features in terms of meaningful text information. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…Then, in order to cope with the limitations of the existing artificial intelligence (AI) based methods, optimized gene expression programming (GEP) is applied to precisely formulate the relationships between historical data and EEC of ASEAN-5 countries. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
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A Constrained Optimization based Extreme Learning Machine for noisy data regression
Published 2023“…Artificial intelligence; Benchmarking; Data handling; Knowledge acquisition; Lagrange multipliers; Learning systems; Optimization; Regression analysis; Benchmark data; Constrained optimization methods; Data regression; Extreme learning machine; Kernel function; Noisy data; Optimization problems; Support vector regression (SVR); Constrained optimization; nitric oxide; algorithm; Article; artificial intelligence; artificial neural network; classifier; combustion; entropy; exhaust gas; extreme learning machine; fuzzy system; generalized regression neural network; generalized regression neural network and fuzzy art; housing; kernel method; logistic regression analysis; machine learning; Malaysia; priority journal; probabilitistic entropy based neural network; process optimization; radial based function; regression analysis; support vector machine…”
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Systematic review on ai-blockchain based e-healthcare records management systems
Published 2022“…Combining AI and blockchain technology can handled some of the drawbacks of these two technical ecosystems effectively. AI algorithms rely on data or information to learn, analyze, and reach conclusions. …”
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