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Wyświetlanie 1-15 z 221
Tytuł:
Game Strategies of Ship in the Collision Situations
Autorzy:
Lisowski, J.
Powiązania:
https://bibliotekanauki.pl/articles/117558.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
game theory
Game Ship Control (GSC)
Collision Situation
MATLAB
Safe Ship Trajectory
Simulation Research
Neural Ship’s Domain
Algorithm
Opis:
The paper introduced the basic model of process of safe ship control in a collision situation using a game model with j objects, which includes non-linear state equations and non-linear, time varying constraints of the state variables as well as the quality game control index in the forms of the game integral payment and the final payment. Approximated model of the process control as the model of multi-step matrix game in the form of dual linear programming problem has been adopted here. The Game Ship Control GSC computer program has been designed in the Matlab/Simulink software in order to determine the own ship’s safe trajectory. These considerations have been illustrated with examples of a computer simulation using an GSC program for determining the safe ship's trajectory in real navigational situation. Simulation research were passed for five sets of strategies of the own ship and met ships.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2014, 8, 1; 69-77
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Structural damage detection in moving load problem using JRNNs based method
Autorzy:
Jena, Shakti P.
Parhi, Dayal R.
Powiązania:
https://bibliotekanauki.pl/articles/279388.pdf
Data publikacji:
2019
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
Jordan’s Recurrent Neural Networks (JRNNs)
crack depth
crack location
Opis:
Damage detection in a structure using the vibration signature is a quiet smart method for condition monitoring of the structure. In this problem, the Recurrent Neural Networks (RNNs) based method has been implemented for damage detection in the moving load problem as an inverse method. A multi-cracked simply supported beam under a traversing load has been considered for the present problem. The localization and severities of the supervised cracks on the structure are determined using the adapted Jordan’s Recurrent Neural Networks (JRNNs) approach. The mechanism of Levenberg-Marquardt’s back propagation algorithm has been implemented to train the networks. To check the adoptability of the proposed JRNNs method, numerical analyses along with laboratory test verifications have been conducted and found to be well emerged.
Źródło:
Journal of Theoretical and Applied Mechanics; 2019, 57, 3; 665-676
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural modeling of plant tissue cultures: a review
Autorzy:
Zielinska, S.
Kepczynska, E.
Powiązania:
https://bibliotekanauki.pl/articles/81293.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial neural network
biomass
plant tissue
neural model
tissue culture
in vitro condition
micropropagation
radial neural network
neural network
somatic embryo
Źródło:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology; 2013, 94, 3
0860-7796
Pojawia się w:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modelling of hemodialysis: regression versus neural model
Autorzy:
Szmajda, R.
Szczepaniak, P. S.
Powiązania:
https://bibliotekanauki.pl/articles/333709.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
hemodializy
sieci nuronowe
haemodialysis
neural network
Opis:
In the paper, evaluation of two approaches to modelling of hemodialysis is performed. Results obtained by regression are compared to those generated by neural models. Differences in the modelling quality are small. Both models shown the same qualitative dependencies between analyzed parameters.
Źródło:
Journal of Medical Informatics & Technologies; 2004, 7; KB41-46
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of artificial neural network and genetic algorithm to healthcarewaste prediction
Autorzy:
Arabgol, S.
Ko, H. S.
Powiązania:
https://bibliotekanauki.pl/articles/91848.pdf
Data publikacji:
2013
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
artificial neural network
ANN
application
hospital
genetic algorithm
GA
healthcare waste
Opis:
Prompt and proper management of healthcare waste is critical to minimize the negative impact on the environment. Improving the prediction accuracy of the healthcare waste generated in hospitals is essential and advantageous in effective waste management. This study aims at developing a model to predict the amount of healthcare waste. For this purpose, three models based on artificial neural network (ANN), multiple linear regression (MLR), and combination of ANN and genetic algorithm (ANN-GA) are applied to predict the waste of 50 hospitals in Iran. In order to improve the performance of ANN for prediction, GA is applied to find the optimal initial weights in the ANN. The performance of the three models is evaluated by mean squared errors. The obtained results have shown that GA has significant impact on optimizing initial weights and improving the performance of ANN.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2013, 3, 4; 243-250
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Selected problem of structure optimization for Artificial Neural Networks with forward connections
Autorzy:
Płaczek, S.
Powiązania:
https://bibliotekanauki.pl/articles/376117.pdf
Data publikacji:
2014
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
artificial neural network
network structure
structure optimization
Opis:
The problem of Artificial Neural Network (ANN) structure optimization related to the definition of optimal number of hidden layers and distribution of neurons between layers depending on selected optimization criterion and inflicted constrains. The article presents the resolution of the optimization problem. The function describing the number of subspaces is given, and the minimum number of layers as well as the distribution of neurons between layers shall be found.
Źródło:
Poznan University of Technology Academic Journals. Electrical Engineering; 2014, 80; 191-197
1897-0737
Pojawia się w:
Poznan University of Technology Academic Journals. Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary computing in operational research for two-layer neural networks
Autorzy:
Płaczek, S.
Powiązania:
https://bibliotekanauki.pl/articles/94935.pdf
Data publikacji:
2017
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
evolutionary algorithm
neural network
optimization algorithm
mutation operator
crossover operator
Opis:
Considering the non-linear characteristics of the activation functions, the entire task is multidimensional and non-linear with a multimodal target function. Implementing evolutionary computing in the multimodal optimization tasks gives developers new and effective tools for seeking the global minimum. A developer has to find the optimal and simple transformation between the realization of a phenotype and a genotype. In the article, a two-layer neural network is analysed. In the first step, the population is created. In the main algorithm loop, a parent selection mechanism is used together with the fitness function. To evaluate the quality of evolutionary computing process different measured characteristics are used. The final results are depicted using charts and tables.
Źródło:
Information Systems in Management; 2017, 6, 2; 119-130
2084-5537
2544-1728
Pojawia się w:
Information Systems in Management
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial neural network modelling to predict optimum power consumption in wood machining
Autorzy:
Tiryaki, S.
Malkocoglu, A.
Ozsahin, S.
Powiązania:
https://bibliotekanauki.pl/articles/52411.pdf
Data publikacji:
2016
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Technologii Drewna
Tematy:
artificial neural network
modelling
optimization
power consumption
wood processing
planing
wood product
Źródło:
Drewno. Prace Naukowe. Doniesienia. Komunikaty; 2016, 59, 196
1644-3985
Pojawia się w:
Drewno. Prace Naukowe. Doniesienia. Komunikaty
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modified neural network based cascaded control for product composition of reactive distillation
Autorzy:
Sakhre, V.
Jain, S.
Sapkal, V. S.
Agarwal, D. P.
Powiązania:
https://bibliotekanauki.pl/articles/778231.pdf
Data publikacji:
2016
Wydawca:
Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
Tematy:
composition
inferential control
neural network
reactive distillation
soft sensor
Opis:
In this research work, neural network based single loop and cascaded control strategies, based on Feed Forward Neural Network trained with Back Propagation (FBPNN) algorithm is carried out to control the product composition of reactive distillation. The FBPNN is modified using the steepest descent method. This modification is suggested for optimization of error function. The weights connecting the input and hidden layer, hidden and output layer is optimized using steepest descent method which causes minimization of mean square error and hence improves the response of the system. FBPNN, as the inferential soft sensor is used for composition estimation of reactive distillation using temperature as a secondary process variable. The optimized temperature profile of the reactive distillation is selected as input to the neural network. Reboiler heat duty is selected as a manipulating variable in case of single loop control strategy while the bottom stage temperature T9 is selected as a manipulating variable for cascaded control strategy. It has been observed that modified FBPNN gives minimum mean square error. It has also been observed from the results that cascaded control structure gives improved dynamic response as compared to the single loop control strategy.
Źródło:
Polish Journal of Chemical Technology; 2016, 18, 2; 111-121
1509-8117
1899-4741
Pojawia się w:
Polish Journal of Chemical Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Characterization of material defects using active thermography and an artificial neural network
Autorzy:
Dudzik, S.
Powiązania:
https://bibliotekanauki.pl/articles/221055.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
active thermography
non-destructive testing
defect characterization
neural networks
Opis:
In the paper a method using active thermography and a neural algorithm for material defect characterization is presented. Experimental investigations are conducted with the stepped heating method, so-called time-resolved infrared radiometry, for the test specimen made of a material with low thermal diffusivity. The results of the experimental investigations were used in simulations of artificial neural networks. Simulations are performed for three datasets representing three stages of the heating process occurring in the investigated sample. In this work, the simulation research aimed to determine the accuracy of defect depth estimation with the use of the mentioned algorithm is descibed.
Źródło:
Metrology and Measurement Systems; 2013, 20, 3; 491-500
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy and Neural Control of an Induction Motor
Autorzy:
Denai, M., A.
Attia, S. A.
Powiązania:
https://bibliotekanauki.pl/articles/908003.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
automatyka
fuzzy control
neural networks
induction motor
vector control
speed observer
Opis:
This paper presents some design approaches to hybrid control systems combining conventional control techniques with fuzzy logic and neural networks. Such a mixed implementation leads to a more effective control design with improved system performance and robustness. While conventional control allows different design objectives such as steady state and transient characteristics of the closed loop system to be specified, fuzzy logic and neural networks are integrated to overcome the problems with uncertainties in the plant parameters and structure encountered in the classical model-based design. Induction motors are characterised by complex, highly non-linear and time-varying dynamics and inaccessibility of some states and outputs for measurements, and hence can be considered as a challenging engineering problem. The advent of vector control techniques has partially solved induction motor control problems, because they are sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Fuzzy logic and neural network-based controllers are considered as potential candidates for such an application. Three control approaches are developed and applied to adjust the speed of the drive system. The first control design combines the variable structure theory with the fuzzy logic concept. In the second approach neural networks are used in an internal model control structure. Finally, a fuzzy state feedback controller is developed based on the pole placement technique. A simulation study of these methods is presented. The effectiveness of these controllers is demonstrated for different operating conditions of the drive system.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2002, 12, 2; 221-233
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Gap Filling of Daily Sea Levels by Artificial Neural Networks
Autorzy:
Pashova, L.
Koprinkova-Hristova, P. D.
Popova, S.
Powiązania:
https://bibliotekanauki.pl/articles/116147.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
artificial neural network (ANN)
hydrography
Black Sea
Opis:
In the recent years, intelligent methods as artificial neural networks are successfully applied for data analysis from different fields of the geosciences. One of the encountered practical problems is the availability of gaps in the time series that prevent their comprehensive usage for the scientific and practical purposes. The article briefly describes two types of the artificial neural network (ANN) architectures ‐ Feed‐ Forward Backpropagation (FFBP) and recurrent Echo state network (ESN). In some cases, the ANN can be used as an alternative on the traditional methods, to fill in missing values in the time series. We have been conducted several experiments to fill the missing values of daily sea levels spanning a 5‐years period using both ANN architectures. A multiple linear regression for the same purpose has been also applied. The sea level data are derived from the records of the tide gauge Burgas, which is located on the western Black Sea coast. The achieved results have shown that the performance of ANN models is better than that of the classical one and they are very promising for the real‐time interpolation of missing data in the time series.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2013, 7, 2; 225-232
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Head-Related Transfer Function Selection Using Neural Networks
Autorzy:
Yao, S.-N.
Collins, T.
Liang, C.
Powiązania:
https://bibliotekanauki.pl/articles/176307.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
head-related transfer function
neural networks
localisation
music
audio
anthropometry
pinna
Opis:
In binaural audio systems, for an optimal virtual acoustic space a set of head-related transfer functions (HRTFs) should be used that closely matches the listener’s ones. This study aims to select the most appropriate HRTF dataset from a large database for users without the need for extensive listening tests. Currently, there is no way to reliably reduce the number of datasets to a smaller, more manageable number without risking discarding potentially good matches. A neural network that estimates the appropriateness of HRTF datasets based on input vectors of anthropometric measurements is proposed. The shapes and sizes of listeners’ heads and pinnas were measured using digital photography; the measured anthropometric parameters form the feature vectors used by the neural network. A graphical user interface (GUI) was developed for participants to listen to music transformed using different HRTFs and to evaluate the fitness of each HRTF dataset. The listening scores recorded were the target outputs used to train the neural networks. The aim was to learn a mapping between anthropometric parameters and listener’s perception scores. Experimental validations were performed on 30 subjects. It is demonstrated that the proposed system produces a much more reliable HRTF selection than previously used methods.
Źródło:
Archives of Acoustics; 2017, 42, 3; 365-373
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On the topological properties of the certain neural networks
Autorzy:
Liu, J.-B.
Zhao, J.
Wang, S.
Javaid, M.
Cao, J.
Powiązania:
https://bibliotekanauki.pl/articles/91804.pdf
Data publikacji:
2018
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
neural network
topological indices
graph theory
Opis:
A topological index is a numeric quantity associated with a network or a graph that characterizes its whole structural properties. In [Javaid and Cao, Neural Computing and Applications, DOI 10.1007/s00521-017-2972-1], the various degree-based topological indices for the probabilistic neural networks are studied. We extend this study by considering the calculations of the other topological indices, and derive the analytical closed formulas for these new topological indices of the probabilistic neural network. Moreover, a comparative study using computer-based graphs has been carried out first time to clarify the nature of the computed topological descriptors for the probabilistic neural networks. Our results extend some known conclusions.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2018, 8, 4; 257-268
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of adsorption efficiencies of Ni (II) in aqueous solutions with perlite via artificial neural networks
Autorzy:
Turp, S. M.
Powiązania:
https://bibliotekanauki.pl/articles/204724.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
wastewater
treatment efficiency
adsorption
perlite
artificial neural network
Opis:
This study investigates the estimated adsorption efficiency of artificial Nickel (II) ions with perlite in an aqueous solution using artificial neural networks, based on 140 experimental data sets. Prediction using artificial neural networks is performed by enhancing the adsorption efficiency with the use of Nickel (II) ions, with the initial concentrations ranging from 0.1 mg/L to 10 mg/L, the adsorbent dosage ranging from 0.1 mg to 2 mg, and the varying time of effect ranging from 5 to 30 mins. This study presents an artificial neural network that predicts the adsorption efficiency of Nickel (II) ions with perlite. The best algorithm is determined as a quasi-Newton back-propagation algorithm. The performance of the artificial neural network is determined by coefficient determination (R2), and its architecture is 3-12-1. The prediction shows that there is an outstanding relationship between the experimental data and the predicted values.
Źródło:
Archives of Environmental Protection; 2017, 43, 4; 26-32
2083-4772
2083-4810
Pojawia się w:
Archives of Environmental Protection
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 221

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