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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…An aid to this is the association rule learning (ARL) paradigm, whose models are computationally inexpensive and do not require a long training time. Therefore, this paper proposes an ARL-based intelligent Behavioural Trust Model (iBUST) for securing the CPPS. …”
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Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki
Published 2014“…These results confirm that, for all the networks the Levenberg-Marquardt algorithm is the most effective algorithm to model the groundwater level. …”
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning
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Stereo Camera-Based Aerial Target Geolocation in a Ground-Based Platform Environment
Published 2024thesis::master thesis -
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Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq
Published 2023“…To overcome these challenges, the current research aims to develop a SpatioTemporal Decision-Making (STDM) model based on Geospatial Artificial Intelligence (GeoAI) to locate onshore wind-solar hybrid plants. …”
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Towards Autonomous Farming -A Novel Scheme based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control
Published 2022“…To this end, several models are proposed in the literature that are based on a selected artificial intelligence (AI) algorithm which is once trained and then deployed. …”
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Towards Autonomous Farming -A Novel Scheme based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control
Published 2022“…To this end, several models are proposed in the literature that are based on a selected artificial intelligence (AI) algorithm which is once trained and then deployed. …”
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Toward Autonomous Farming - A Novel Scheme Based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control
Published 2022“…To this end, several models are proposed in the literature that is based on a selected artificial intelligence (AI) algorithm which is once trained and then deployed. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The obtained result from the twelve deployed ML algorithms for the standalone intelligent ML-APS relay classifier modification without communication medium adoption for transmitting and receiving the updated relay operation settings during network configuration changes. …”
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2TSS: Two-tier semantic segmentation framework with enhancement for hotspot detection of solar photovoltaic thermal images
Published 2025“…Recently, intelligence-based hotspot detection has been widely used in solar photovoltaic (PV) image applications. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…The ANNs trained by the optimized DA also achieve higher accuracy than those trained by some other swarm intelligence algorithms. …”
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Integration of dual intelligent algorithms in shunt active power filter
Published 2013“…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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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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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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