Search Results - (( its application learning algorithm ) OR ( variable activation function algorithm ))
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS
Published 2011“…The final architecture for this system has been explored after investigation of various main neural network topology combinations which include one and two hidden layers, one to ten neurons for each hidden layer, three types of activation function, and four types of multidimensional minimization training algorithms. …”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
Published 2022“…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…Utilization of soft-computing algorithms in the operation of Shunt Active Power Filters (SAPFs) becomes a latest trend. …”
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5
Real time De-mixing system based on LMS adaptive algorithm for blind two source signals separation
Published 2007“…The time variant mixing matrix based on random vector with time variable elements are made. Several simulations obtain optimum results of implemented algorithm. …”
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network
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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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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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9
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. …”
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MotionSure: a cloud-based algorithm for detection of injected object in data in motion
Published 2017“…Mostly, the Man In The Middle (MITM) attack happens in this stage by hijacking active session variables, manipulating files and objects. …”
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Proceeding Paper -
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A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments
Published 2021“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
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A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments
Published 2021“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
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A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments
Published 2021“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
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Ensemble dual recursive learning algorithms for identifying flow with leakage
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Active force control with iterative learning control algorithm for a vehicle suspension
Published 2013“…The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. …”
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Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding
Published 2007“…The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The obtained results show that the Quasi-Newton based algorithm has better performance as compared to the other two algorithms.…”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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