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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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Article -
2
Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…Motivating by these drawbacks, this research proposes a new model of dialogue act recognition in which dynamic Bayesian machine learning is applied to induce dynamic Bayesian networks models from task-oriented dialogue corpus using sets of lexical cues selected automatically by means of new variable length genetic algorithm. …”
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Thesis -
3
Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024Subjects:Article -
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Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz
Published 2022“…The purpose of this study is to use machine learning (ML) and deep learning (DL) algorithms to predict and identify variables linked to short and long-term mortality in Asian STEMI and NSTEMI/UA patients and to compare these results to a conventional risk score. …”
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6
Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
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Proceedings -
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Prediction of Machine Failure by Using Machine Learning Algorithm
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Final Year Project -
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction
Published 2022“…Particle Swarm Optimization is useful to optimize the best variables combination for automating the features selection in machine learning models. …”
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Ensemble dual recursive learning algorithms for identifying flow with leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The application of abruptly enlarged flows to adjust the drag of aerodynamic vehicles using machine learning models has not been investigated previously. …”
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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…Notably, weight, and Body Mass Index (BMI) exhibit the highest significance among the other variables. Looking ahead, future research could explore enhancing DTs' predictive capabilities in athlete selection by incorporating more variables or employing ensemble learning techniques. …”
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Prediction of monthly rainfall at Senai, Johor using artificial immune system and deep learning neural network
Published 2020“…MLP is a deep learning algorithm used in the Artificial Neural Network (ANN). …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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Thesis -
16
Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Machine learning models have been effectively applied to predict certain variable in several engineering applications where the variable is highly stochastic in nature and complex to identify utilizing the classical mathematical models. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review
Published 2023“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review
Published 2023“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Classifying corporates default and non-default using machine learning Artificial Neural Network: multilayer perceptron / Nur Insyirah Mohamad Radzi, Murni Salina Rosidi and Nur Asy...
Published 2023“…Asset volatility is found to be the most significant independent variable. Therefore, ANN is a machine learning algorithm that uses multiple layers perceptron to solve complex problems and predict analytics.…”
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