Search Results - intelligence based ((((training algorithm) OR (learning algorithm))) OR (learning algorithms))
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Thesis -
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing
Published 2022“…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network
Published 2024“…This study proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. …”
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Overhead view based person counting using deep learning
Published 2022“…Third, the accurate tracking of each detected person is performed using the deep learning based tracking framework, known as DeepSORT. …”
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Final Year Project / Dissertation / Thesis -
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Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman
Published 2012“…Genetic Algorithm (GA) based learning technique provides an alternative way that involves controlling the learning complexity by adjusting the number of weights of the ANN. …”
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Book Section -
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin
Published 2023“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification
Published 2022“…In this study, exhaustive empirical research of the machine learning algorithm for hand posture classification has been established. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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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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