Search Results - (( developing function learning algorithm ) OR ( based applications model algorithm ))
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…This study uses the genetic algorithm radial basis, neural network model, to make judgments on the relationships contained in this sequence and compare and analyze the prediction effect and generalization ability of the model to verify the applicability of the genetic algorithm radial basis, neural network model, based on the modeling of historical data, which may contain linear and nonlinear relationships by itself, so this study uses the genetic algorithm radial basis, neural network model, to make, compare, and analyze judgments on the relationships contained in this sequence.…”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm
Published 2023Conference Paper -
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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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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…Hence, a wide range of studies has been focused on determining the optimal weight values of ANN models and the number of hidden neurons. In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Bio-signal identification using simple growing RBF-network (OLACA)
Published 2007“…These algorithms are developed primarily for applications with fast sampling rate which demands significant reduction in computation load per iteration. …”
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Conference or Workshop Item -
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The work is further extended to developing and integrating the idea of active control of flexible structures into an interactive learning environment. …”
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Chaos search in fourire amplitude sensitivity test
Published 2012“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Chaos Search in Fourier Amplitude Sensitivity Test
Published 2012“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Stock price monitoring system
Published 2024“…This project is a development-based project with deep learning approach for academic purpose. …”
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Final Year Project / Dissertation / Thesis -
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR
Published 2005“…In this project, the algorithm of the tuning method based on Nyquist Stability Criterion is developed first. …”
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Final Year Project -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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