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Research on Multimode Biometric Features Recognition System Adopting Neural Network
2015
Open Cybernetics and Systemics Journal
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Based on this, this paper proposes a efficient multimode biometric face and fingerprint recognition system based on neural network, which provides more efficient identification though choosing a good feature ...
The Adoption of biometric recognition to authenticate a person's identity has greatly improved operational efficiency and the recognition accuracy in comparison with adoption of password or passphrase. ...
The problem for artificial neural network is to understand the structure of an algorithm is very difficult, since too many factors may result in excessive filtration, and the best network structure can ...
doi:10.2174/1874110x01509012508
fatcat:ysxo5sj3mzeztp5sddq3qcjpoq
A Nonlinear System Identification based on Additive Expression Tree Model with Cuckoo Search
2015
International Journal of Hybrid Information Technology
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For finding the optimal structure and parameters of systems, a hybrid evolutionary method integrating a new structure based evolutionary algorithm and cuckoo search is employed. ...
We illustrate some experimental comparisons with neural network, neural network integrating fuzzy system and symbolic regression methods. ...
Acknowledgements This work was supported by the PhD research startup foundation of Zaozhuang University (No.1020702), and the Natural Science Foundation of Shandong Province, China (No.ZR2015PF007). ...
doi:10.14257/ijhit.2015.8.8.39
fatcat:f5xxc47s5rc4fjd73rrqc25mhy
Artificial Neural Network based String Matching Algorithms for Species Classification A Preliminary Study and Experimental Results
2012
International Journal of Computer Applications
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The preliminary research in the area of applications of neural networks and pattern matching algorithms in species classification is presented. ...
Artificial neural networks for classification and different pattern matching algorithms for matching the given DNA patterns or strings with the existing DNA sequences available in the databases are specifically ...
Predict® combines neural network technology with genetic algorithms, statistics, and fuzzy logic to automatically find optimal or near-optimal solutions for a wide range of problems. ...
doi:10.5120/8270-1832
fatcat:azp4b4yxezhq7ecku3k6vgquli
Improvement of the Izhikevich model based on the rat basolateral amygdala and hippocampus neurons, and recognition of their possible firing patterns
[article]
2021
arXiv
pre-print
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2019 pre-print arXiv:1910.11380v2 fatcat:mu53q52yhndbvknmwl6crf73giOther Versions
In order to optimize the Izhikevich model parameters, the genetic algorithm is used. ...
Improving the Izhikevich model for adapting with the neuronal activity of rat brain with great accuracy would make the model effective for future neural network implementations. ...
in simulation of neural networks, based on the biological evidences. ...
arXiv:1910.11380v3
fatcat:x464kvuatbdajckfs7nckslxyi
Research on Quality Anomaly Recognition Method Based on Optimized Probabilistic Neural Network
2020
Shock and Vibration
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chart data by probabilistic neural network (PNN) optimized by improved genetic algorithm, which made up deficiencies of SPC control charts in practical application. ...
Finally, the above method was validated by a simulation experiment and proved to be the most effective method compared with traditional BP neural network, single PNN, PCA-PNN without parameters optimized ...
used by traditional neural networks, and PNN is a kind of forward propagation algorithm without feedback. e structure of a typical probabilistic neural network is shown in Figure 7 . ...
doi:10.1155/2020/6694732
fatcat:pstvmytkffhv7gemtmpwwwpe3u
Germinal Center Optimization Applied to Neural Inverse Optimal Control for an All-Terrain Tracked Robot
2017
Applied Sciences
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There is a number of system identification techniques, to name a few: neural networks, fuzzy logic, auxiliary model, hierarchical identification. ...
In the Neural Inverse Optimal Control (NIOC) scheme, a neural identifier, based on Recurrent High Orden Neural Network (RHONN) trained with an extended kalman filter algorithm, is used to obtain a model ...
Hernandez-Vargas designed the GCO algorithm, the objective function and perform the optimization.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app8010031
fatcat:u2f4mlnbc5dhhftig4wmauaovm
CONTROL AND SOFT SENSING STRATEGIES FOR A WASTEWATER TREATMENT PLANT USING A NEURO-GENETIC APPROACH
2020
Computers and Chemical Engineering
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The methodology proposed in this study uses neural networks as a soft-sensor for on-line prediction of the effluent quality and as an identification model of the plant dynamics, all under a neuro-genetic ...
In this paper, a machine learning-based control strategy is proposed for optimizing both the consumption and the number of regulation violations of a biological wastewater treatment plant. ...
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper ...
doi:10.1016/j.compchemeng.2020.107146
fatcat:pfb4cr662ffabmkcz6l76454oy
Genetic Optimization of Neural Networks for Person Recognition based on the Iris
2012
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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Optimization of the neural networks was performed with genetic algorithms (GAs), which are essentially a method that creates a population of individuals to find the most appropriate one by simulating evolution ...
Artificial neural networks are inspired by the architecture of the biological nervous system, which consists of a large number of relatively simple neurons that work in parallel to facilitate rapid decision-making ...
Optimization of the Architecture To optimize the modular neural network a genetic algorithm was used to find the optimal architecture and an appropriate recognition rate. ...
doi:10.12928/telkomnika.v10i2.167
fatcat:bz4c2ftevzhnjaphdkomtwgwbq
Genetic Optimization of Neural Networks for Person Recognition based on the Iris
2012
TELKOMNIKA Indonesian Journal of Electrical Engineering
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Optimization of the neural networks was performed with genetic algorithms (GAs), which are essentially a method that creates a population of individuals to find the most appropriate one by simulating evolution ...
Artificial neural networks are inspired by the architecture of the biological nervous system, which consists of a large number of relatively simple neurons that work in parallel to facilitate rapid decision-making ...
Optimization of the Architecture To optimize the modular neural network a genetic algorithm was used to find the optimal architecture and an appropriate recognition rate. ...
doi:10.11591/telkomnika.v10i2.684
fatcat:3ex4m6z6lff4jaun5lbdr3btsm
Genetic Optimization of Neural Networks for Person Recognition Based on the Iris
2012
TELKOMNIKA (Telecommunication Computing Electronics and Control)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Optimization of the neural networks was performed with genetic algorithms (GAs), which are essentially a method that creates a population of individuals to find the most appropriate one by simulating evolution ...
Artificial neural networks are inspired by the architecture of the biological nervous system, which consists of a large number of relatively simple neurons that work in parallel to facilitate rapid decision-making ...
Optimization of the Architecture To optimize the modular neural network a genetic algorithm was used to find the optimal architecture and an appropriate recognition rate. ...
doi:10.12928/telkomnika.v10i2.800
fatcat:x45putzizzesfemh2k2im6tnke
A Decision and Control System Mimicking a Skilled Grower's Thinking Process for Dynamic Optimization of the Storage Environment
2003
Environment Control in Biology
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Here,
because
an optimal
value
is given
by
(a) Three-layered neural network
(b) Flow chart of the genetic algorithm
Fig. 2 The neural
network
and genetic algorithm
used in decision
system ...
., relative humidity), and a genetic algorithm for searching for the optimal i-step set points of the storage environment. ...
doi:10.2525/ecb1963.41.221
fatcat:l2ibguangfbedn5p66hgwnydny
Recent Developments in Damage Identification of Structures Using Data Mining
2017
Latin American Journal of Solids and Structures
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Acknowledgements The authors would like to express their sincere thanks to University of Malaya (UM) and the Ministry of Education (MOE), Malaysia for the support given through research grants PG144-2016A ...
) Damage identification in a continuous bridge using neural networks (Bagchi et al. 2010 ) Damage identification of a building using wavelet neural network (Hung et al. 2003 ) Damage identification using ...
using fuzzy wavelet neural network (Jiang and Mahadevan 2008a) Prediction of the cracking pattern of masonry wallet using ANN (Zhang et al. 2010) Comparison of the accuracy between RealAdaBoost algorithm ...
doi:10.1590/1679-78254378
fatcat:s2q7y2psz5e7tfc7lsf4o3fz34
Data mining based damage identification using imperialist competitive algorithm and artificial neural network
2018
Latin American Journal of Solids and Structures
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In this study, to predict the damage severity of single-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural ...
Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. ...
Acknowledgements The authors would like to express their sincere thanks to University of Malaya (UM) and the Ministry of Education (MOE), Malaysia for the support given through research grants PG144-2016A ...
doi:10.1590/1679-78254546
fatcat:d3udwhjp6fge3mxrziiys6b4b4
Daily Global Solar Radiation Modeling Using Multi-Layer Perceptron (Mlp) Neural Networks
2011
Zenodo
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Predict daily global solar radiation (GSR) based on meteorological variables, using Multi-layer perceptron (MLP) neural networks is the main objective of this study. ...
The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. ...
Predicting of global solar radiation can also be investigated with neural networks trained with intelligent optimization techniques like Particle Swarm Optimization, Bees Algorithm and etc. ...
doi:10.5281/zenodo.1077088
fatcat:sbfkotxq3fdo3ecd6ymqfnurou
Analysis of Tomato Leaf Disease Identification Techniques
2021
Journal of Computer Science and Engineering (JCSE)
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Convolutional neural networks with backpropagation algorithms have achieved great success in diagnosing various plant diseases. ...
Under different conditions, the accuracy of the plant identification system is much lower than expected by algorithms. ...
ADAM optimization algorithm is used with categorical cross-entropy loss metric to train the neural network. ...
doi:10.36596/jcse.v2i2.171
fatcat:gj7x2qkg7rawbbpzjpxbx5cyti
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