Search Results - (( simultaneous implementation learning algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Design and development of cooperative simultaneous localization and mapping integrated with neural network for mobile robot
Published 2024“…Autonomous cooperating mobile robots is one of technological advancement in enabling autonomy in search and rescue task (SaR). While, simultaneous localization and mapping (SLAM) algorithm is one of a key element to enable autonomous navigation. …”
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3
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Distributed Multi-Feature Recognition Scheme for Greyscale Images
Published 2011“…Furthermore, our approach implements single-cycle learning known as collaborative-comparison learning where new patterns are continuously stored using collaborative approach without affecting previously stored patterns. …”
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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10
A study of the high-performance computing parallelism in solving complexity of meteorology data and calculations
Published 2024“…Further issues can be studied for integrating big data analytics and machine learning into HPC computing architectures.…”
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Feature and Instance selection via cooperative PSO
Published 2011“…Although, some work has been done to implement the feature and instance selection simultaneously, this work has focused on mainly the classification problem. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RSNN implements a novel approximation transform. The basic design for the network is provided together with the learning rules. …”
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13
A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow
Published 2025“…An optical flow-based preprocessing algorithm synchronized motion features in recorded video inputs with measured vibration labels, improving measurement accuracy. …”
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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust
Published 2022“…The experimental data has been divided into the training set and testing set in the proportion of 85 (for training) and 15 (for testing) respectively. A machine learning artificial neural network approach with Levenberg-Marquardt algorithm is implemented to obtain the predictive model for MIT of aluminium dust for both the particle size ranges (100â��63 µm, 50â��32 µm). …”
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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust
Published 2022“…The experimental data has been divided into the training set and testing set in the proportion of 85 (for training) and 15 (for testing) respectively. A machine learning artificial neural network approach with Levenberg-Marquardt algorithm is implemented to obtain the predictive model for MIT of aluminium dust for both the particle size ranges (100â��63 µm, 50â��32 µm). …”
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Problem restructuring in interger programming for reduct searching
Published 2003“…Simultaneously the approach adheres to an essential criterion of the original method. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…However, due to the drawbacks of the conventional algorithm as well as the heuristic algorithms handling complicated and multi-objective reservoir optimisation, the advantages of the strategy of simultaneous exploration and exploitation led to the decision to utilise meta-heuristic algorithms in this study. …”
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