Search Results - (( model application learning algorithm ) OR ( its applications using algorithm ))*
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A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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Proceeding Paper -
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Ensemble dual recursive learning algorithms for identifying flow with leakage
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Conference or Workshop Item -
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…MLPs are well-known tools used in nonlinear system identification, statistical modelling, adaptive control signal, image processing and for many applications. …”
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Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023
Published 2024“…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. …”
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Classification model for water quality using machine learning techniques
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model
Published 2025“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023“…Backpropagation; Gradient methods; Neural networks; Artificial neural network models; Complex applications; Exploration and exploitation; Gradient-based learning; Industry applications; Meta heuristic algorithm; Meta-heuristic search algorithms; Near-optimal solutions; Optimization…”
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Deep learning model for predicting and detecting overlapping symptoms of cardiovascular diseases in hospitals of UAE
Published 2012“…However, DL has number of weaknesses as well, including difficulty in interpreting its examples (the 'black-box' criticism), its requirement for multiple training data, no specificity in design, no data-usefulness in training, limited use in experimental models, and so on. …”
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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A review of hybrid deep learning applications for streamflow forecasting
Published 2024Subjects:Review -
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing
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Final Year Project / Dissertation / Thesis -
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…The FFNN training process which is an optimization task to find the optimal controlling parameters (weights and biases) is considered as the main issues in any model performance. Due to that, many algorithms employ different training algorithms to guide the network for providing an accurate result with less training and testing error. …”
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Predictive modelling of nanofluids thermophysical properties using machine learning
Published 2021“…The optimization of the machine learning parameters was conducted using the Genetic Algorithm or the Bayesian Optimization Algorithm techniques. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…The proposed algorithm employs a combined model that uses two different measures (nonconformity metric measures and Local Distance-based Outlier Factor (LDOF)) to improve its detection ability. …”
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