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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing
Published 2019“…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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Energy efficient path reconstruction in wireless sensor network using iPath
Published 2019“…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…Two controller design formulations are proposed. The first controller design is formulated so as to allow on-line modeling, controller design and implementation and thus, yield a self-tuning control algorithm. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…The proposed deep reinforcement learning algorithm, which integrates an artificial neural network with traditional reinforcement learning, was formulated based on the optimisation objective by manipulating only the substrate feeding rate. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
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Final Year Project / Dissertation / Thesis -
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms
Published 2023Article -
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The effect of human learning and forgetting on fuzzy EOQ model with backorders / Nima Kazemi
Published 2017“…In order to optimize the models and derive solutions, an optimization algorithm was developed for the first model and applied later throughout the study. …”
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Sign language recognition using deep learning through LSTM and CNN
Published 2023“…The objectives of this thesis are to extract features from the dataset for sign language recognition model and the formulation of deep learning models and the classification performance to carry out the sign language recognition. …”
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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging
Published 2021“…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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Extending the decomposition algorithm for support vector machines training
Published 2003“…One can design a dedicated optimizer that will take full advantage of the specific nature of the QP problem in SVM training. The decomposition algorithm developed by Osuna et al. (1997a) reduces the training cost to an acceptable level. …”
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Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron
Published 2013“…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo...
Published 2017“…The optimum topologies were selected among the learning algorithms trained with lowest root mean square values. …”
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