Search Results - (( variable activation function algorithm ) OR ( based applications testing algorithm ))
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1
Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah
Published 2017“…Finally, the development of prototype microcontroller-based CAWS featuring MSDG activation algorithm has been developed. The accuracy and the functionality of the system has been tested and validated. …”
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2
Design of artificial intelligence based speed estimator for DC drives / Pauziah Saleh
Published 2006“…For this purpose, the Lavenberg-Marquardt back propagation algorithm was used. A standard three layer feed-forward neural network with tan-sigmoid (tansig) activation functions in the hidden layer and purelin at the output layer is used for this test. …”
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3
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Three algorithms of Linear (PURELIN), hyperbolic tangent sigmoid (TANSIG) and logistic sigmoid (LOGSIG) activation functions were selected for output layer. …”
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4
Assessment of proposed lateral resistance system used with framed structures
Published 2016“…Numerous studies have been conducted, specifically in structural engineering, to develop and evaluate the dynamic performance of energy dissipation systems based on the variable stiffness concept, such as active, semi-active, and passive variable stiffness methods. …”
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5
A review of slicing techniques in software engineering
Published 2015“…Software testing is regarded as an activity to evaluate the functionality and features of a system. …”
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Design of Artificial Neural Network (ANN) based rotor speed estimator for DC drives / Siti Mutrikah Abd Mokhsin
Published 2002“…It is satisfied that, even the application of ANN rotor speed feedback in closed loop system, the speed obtained is variable speed. …”
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7
Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…Generally, optimization computational and mathematical methods are designed for finding the best solution of a certain problems that aiming for minimizing or maximizing the objective functions based on the variables and subject to a set of constraints. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of two hidden layers with six and seven neurons in the first and second layers, respectively for xylitol stearate and xylitol palmitate and also seven and five neurons in the first and second layers for xylitol caprate, with hyperbolic tangent sigmoid transfer function. …”
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9
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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10
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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11
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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12
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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13
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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15
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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16
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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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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18
An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…In order to identify the strength and weakness of these algorithms for MC/DC compliant test cases, this research proposes an experimental study involving four neighborhoods based meta-heuristic algorithms. …”
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Analysis of boiler operational variables prior to tube leakage fault by artificial intelligent system
Published 2014“…The results showed that the NN with two hidden layers performed better than one hidden layer using Levenberg-Maquardt training algorithm. Moreover, it was noticed that hyperbolic tangent function for input and output nodes performed better than other activation function types. …”
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