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Wyświetlanie 1-15 z 309
Tytuł:
Research and applications of artificial neural networks in spatial analysis: Review
Autorzy:
Garczyńska, Ilona
Powiązania:
https://bibliotekanauki.pl/articles/29521035.pdf
Data publikacji:
2023
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
spatial analysis
GIS
artificial neural network
artificial intelligence
geosciences
Opis:
The conducted review presents the possibility of using artificial neural networks in sectors related to environmental protection, agriculture, forestry, land uses, groundwater and bathymetric. Today there is a lot of research in these areas with different research methodologies. The result is the improvement of decision-making processes, design, and prediction of certain events that, with appropriate intervention, can prevent severe consequences for society. The review shows the capabilities to optimize and automate the processes of modeling urban and land dynamics. It examines the forecasts of assessment of the damage caused by natural phenomena. Detection of environmental changes via the analysis of certain time intervals and classification of objects on the basis of different images is presented. The practical aspects of this work include the ability to choose the correct artificial neural network model depending on the complexity of the problem. This factor is a novel element since previously reviewed articles did not encounter a study of the correlation between the chosen model or algorithm, depending on the use case or area of the problem. This article seeks to outline the reason for the interest in artificial intelligence. Its purpose is to find answers to the following questions: How can artificial neural networks be used for spatial analysis? What does the implementation of detailed algorithms depend on? It is proved that an artificial intelligence approach can be an effective and powerful tool in various domains where spatial aspects are important.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2023, 74 (146); 35-45
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Potential and use of the googlenet ann for the purposes of inland water ships classification
Autorzy:
Bobkowska, Katarzyna
Bodus-Olkowska, Izabela
Powiązania:
https://bibliotekanauki.pl/articles/1573774.pdf
Data publikacji:
2020
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship classification
image classification
geoinformatics
artificial intelligence
artificial neural network
Opis:
This article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and Identification (SHREC) project. The image repository for the training purposes consists about 6,000 images of different categories of the vessels. Some images were gathered from internet websites, and some were collected by the project’s video cameras. The GoogLeNet network was trained and tested using 11 variants. These variants assumed modifications of image sets representing (e.g., change in the number of classes, change of class types, initial reconstruction of images, removal of images of insufficient quality). The final result of the classification quality was 83.6%. The newly obtained neural network can be an extension and a component of a comprehensive geoinformatics system for vessel recognition.
Źródło:
Polish Maritime Research; 2020, 4; 170-178
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The survey of soft computing techniques for reliability prediction
Autorzy:
Smoczek, J.
Powiązania:
https://bibliotekanauki.pl/articles/246835.pdf
Data publikacji:
2012
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
reliability prediction
artificial intelligence
fuzzy logic
artificial neural network
genetic algorithm
Opis:
The objective of reliability prediction is to estimate a time of upcoming nonoperational state at the current operational state of a system through real-time monitoring operational parameters and/or performances. Hence, the predictive (proactive) maintenance in industrial systems involves operational conditions monitoring and online forecasting the useful life of machines equipment to support the decision-making process in selection of the best maintenance action to be carried out. The advanced warning of the failure possibility can bring the attention of machines operators and maintenance personnel to impending danger, and facilitate planning preventive and corrective operations, as well as inventory managing. This problem has been extensively studied in many scientific works, where the predictive models are based on the data-driven approaches that can be generally divided into statistical techniques (regression, ARMA models, Bayesian probability distribution estimation, etc.), grey system theory, and soft computing methods. The artificial intelligence is frequently addressed to the predictive problem by utilizing the learning capability of artificial neural network (ANN), and possibility of nonlinear mapping using fuzzy rules-based system (FRBS) or recognizing and optimizing data-derived pattern by using evolutionary algorithms. The paper is a survey of intelligent methods for failure prediction, and delivers the review of examples of scientific works presenting the computational intelligence-based approaches to predictive problem.
Źródło:
Journal of KONES; 2012, 19, 3; 407-414
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Polish emotional speech recognition using artifical neural network
Autorzy:
Powroźnik, P.
Powiązania:
https://bibliotekanauki.pl/articles/102146.pdf
Data publikacji:
2014
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
emotional speech
artificial neural network
communication
Opis:
The article presents the issue of emotion recognition based on polish emotional speech analysis. The Polish database of emotional speech, prepared and shared by the Medical Electronics Division of the Lodz University of Technology, has been used for research. The following parameters extracted from sampled and normalised speech signal has been used for the analysis: energy of signal, speaker’s sex, average value of speech signal and both the minimum and maximum sample value for a given signal. As an emotional state a classifier fof our layers of artificial neural network has been used. The achieved results reach 50% of accuracy. Conducted researches focused on six emotional states: a neutral state, sadness, joy, anger, fear and boredom.
Źródło:
Advances in Science and Technology. Research Journal; 2014, 8, 24; 24-27
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modern method based on artificial intelligence for safe control in the marine environment
Autorzy:
Mohamed-Seghir, Gdynia Maritime University, Gdynia, Poland
Powiązania:
https://bibliotekanauki.pl/articles/24201419.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
safe ship's trajectory
collision avoidance
artificial intelligence
artificial neural network
fuzzy logic
evolutionary algorithms
dynamic programming
Opis:
The article presents an approach to formulating a ship control process model in order to solve the problem of determining a safe ship trajectory in collision situations. Fuzzy process properties are included in the model to bring it closer to reality, as in many situations the navigator makes a subjective decision. A special neural network was used to solve the presented problem. This artificial neural network is characterized by minimum and maximum operations when set. In order to confirm the correctness of the operation of the proposed algorithm, the results of the simulations obtained were presented and an discussion was conducted.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 2; 283--288
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evaluating the performance of Extreme Learning Machine technique for ore grade estimation
Autorzy:
Abuntori, Clara Akalanya
Al-Hassan, Sulemana
Mireku-Gyimah, Daniel
Ziggah, Yao Yevenyo
Powiązania:
https://bibliotekanauki.pl/articles/1839059.pdf
Data publikacji:
2021
Wydawca:
Główny Instytut Górnictwa
Tematy:
extreme learning machine
artificial intelligence
artificial neural network
grade estimation
kriging
ELM
sztuczna inteligencja
sztuczna sieć neuronowa
Opis:
Due to the complex geology of vein deposits and their erratic grade distributions, there is the tendency of overestimating or underestimating the ore grade. These estimated grade results determine the profitability of mining the ore deposit or otherwise. In this study, five Extreme Learning Machine (ELM) variants based on hard limit, sigmoid, triangular basis, sine and radial basis activation functions were applied to predict ore grade. The motive is that the activation function has been identified to play a key role in achieving optimum ELM performance. Therefore, assessing the extent of influence the activation functions will have on the final outputs from the ELM has some scientific value worth investigating. This study therefore applied ELMas ore grade estimator which is yet to be explored in the literature. The obtained results from the five ELM variants were analysed and compared with the state-of-the-art benchmark methods of Backpropagation Neural Network (BPNN) and Ordinary Kriging (OK). The statistical test results revealed that the ELM with sigmoid activation function (ELM-Sigmoid) was the best among all the other investigated methods (ELM-Hard limit, ELM-Triangular basis, ELM-Sine, ELM-Radial Basis, BPNN and OK). This is because the ELM-sigmoid produced the lowest MAE (0.0175), MSE (0.0005) and RMSE (0.0229) with highest R2 (91.93%) and R (95.88%) respectively. It was concluded that ELM-Sigmoid can be used by field practitioners as a reliable alternative ore grade estimation technique.
Źródło:
Journal of Sustainable Mining; 2021, 20, 2; 56-71
2300-1364
2300-3960
Pojawia się w:
Journal of Sustainable Mining
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hyperparameter optimization of artificial neural networks to improve the positional accuracy of industrial robots
Autorzy:
Uhlmann, Eckart
Polte, Mitchel
Blumberg, Julian
Li, Zhoulong
Kraft, Adrian
Powiązania:
https://bibliotekanauki.pl/articles/1429023.pdf
Data publikacji:
2021
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
artificial neural network
robot calibration
hyperparameter optimization
Opis:
Due to the rising demand for individualized product specifications and short product innovation cycles, industrial robots gain increasing attention for machining operations as milling and forming. Limitations in their absolute positional accuracy are addressed by enhanced modelling and calibration techniques. However, the resulting absolute positional accuracy stays in a range still not feasible for general purpose milling and forming tolerances. Improvements of the model accuracy demand complex, often not accessible system knowledge on the expense of realtime capability. This article presents a new approach using artificial neural networks to enhance positional accuracy of industrial robots. A hyperparameter optimization is applied, to overcome the downside of choosing an appropriate artificial neural network structure and training strategy in a trial and error procedure. The effectiveness of the method is validated with a heavy-duty industrial robot. It is demonstrated that artificial neural networks with suitable hyperparameters outperform a kinematic model with calibrated geometric parameters.
Źródło:
Journal of Machine Engineering; 2021, 21, 2; 47-59
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Spectral methods in Polish emotional speech recognition
Autorzy:
Powroźnik, P.
Czerwiński, D.
Powiązania:
https://bibliotekanauki.pl/articles/102087.pdf
Data publikacji:
2016
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
artificial neural network
spectrogram
emotional speech recognition
Opis:
In this article the issue of emotion recognition based on Polish emotional speech signal analysis was presented. The Polish database of emotional speech, prepared and shared by the Medical Electronics Division of the Lodz University of Technology, has been used for research. Speech signal has been processed by Artificial Neural Networks (ANN). The inputs for ANN were information obtained from signal spectrogram. Researches were conducted for three different spectrogram divisions. The ANN consists of four layers but the number of neurons in each layer depends of spectrogram division. Conducted researches focused on six emotional states: a neutral state, sadness, joy, anger, fear and boredom. The averange effectiveness of emotions recognition was about 80%.
Źródło:
Advances in Science and Technology. Research Journal; 2016, 10, 32; 73-81
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
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:
Development of smart sorting machine using artificial intelligence for chili fertigation industries
Autorzy:
Abdul Aziz, M. F.
Bukhari, W. M.
Sukhaimie, M. N.
Izzuddin, T.A.
Norasikin, M.A.
Rasid, A. F. A.
Bazilah, N. F.
Powiązania:
https://bibliotekanauki.pl/articles/2141810.pdf
Data publikacji:
2021
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
precision agriculture
artificial neural network
smart fertigation
Opis:
This paper presents an automation process is a need in the agricultural industry specifically chili crops, that implemented image processing techniques and classification of chili crops usually based on their color, shape, and texture. The goal of this study was to develop a portable sorting machine that will be able to segregate chili based on their color by using Artificial Neural Network (ANN) and to analyze the performance by using the Plot Confusion method. A sample of ten green chili images and ten red chili images was trained by using Learning Algorithm in MATLAB program that included a feature extraction process and tested by comparing the performance with a larger dataset, which are 40 samples of chili images. The trained network from 20 samples produced an overall accuracy of 80 percent and above, while the trained network from 40 samples produced an overall accuracy of 85 percent. These results indicate the importance of further study as the design of the smart sorting machine was general enough to be used in the agricultural industry that requires a high volume of chili crops and with other differentiating features to be processed at the same time. Improvements can be made to the sorting system but will come at a higher price.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2021, 15, 4; 44-52
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of an artificial neural network for planning the trajectory of a mobile robot
Autorzy:
Białek, Marcin
Nowak, Patryk
Rybarczyk, Dominik
Powiązania:
https://bibliotekanauki.pl/articles/384525.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
artificial neural network
mobile robot
machine vision
Opis:
This paper presents application of a neural network in the task of planning a mobile robot trajectory. First part contains a review of literature focused on the mobile robots’ orientation and overview of artificial neural networks’ application in area of robotics. In these sections devices and approaches for collecting data of mobile robots environment have been specified. In addition, the principle of operation and use of artificial neural networks in trajectory planning tasks was also presented. The second part focuses on the mobile robot that was designed in a 3D environment and printed with PLA material. The main onboard logical unit is Arduino Mega. Control system consist of 8-bits microcontrollers and 13 Mpix camera. Discussion in part three describes the system positioning capability using data from the accelerometer and magnetometer with overview of data filtration and the study of the artificial neural network implementation to recognize given trajectories. The last chapter contains a summary with conclusions.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 1; 13-23
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Prediction Study on Bremsstrahlung Photon Flux of Tungsten as a Radiological Anode Material by using MCNPX and ANN Modeling
Autorzy:
Tekin, H.
Kara, U.
Manici, T.
Altunsoy, E.
Erguzel, T.
Powiązania:
https://bibliotekanauki.pl/articles/1030108.pdf
Data publikacji:
2017-09
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
artificial neural network
Monte Carlo
medical imaging
Opis:
Medical imaging is a technique that is mostly known as visual representations of the parts of body for clinical scans and analysis. In imaging process for medical purpose there take part radiologists, radiographers/radiology technicians, medical physicists, sonographers, nurses, and engineers. As an apart issue from the medical imaging devices, we can treat X-rays using devices such as radiography, computed tomography, fluoroscopy, dental cone-beam computed tomography, and mammography. All these devices are to perform X-ray using during medical imaging process. An X-ray beam is generated in a vacuum tube that is principally composed of an anode and a cathode material to produce X-ray beams, whose name is X-ray tube. The anode represents the component in which the X-ray beam produced that made from a piece of metal. For decades, tungsten (W) has been used as an anode material of various X-ray tubes. Tungsten has high atomic number and high melting point of 3370°C with low rate of volatilization. In this study, we performed Monte Carlo simulation for flux calculations of W target by using MCNP-X general purpose code and considered result as a data set for artificial neural network. It can be concluded that the results agreed well between Monte Carlo simulation and artificial neural network prediction.
Źródło:
Acta Physica Polonica A; 2017, 132, 3; 433-435
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Monitoring of the average cutting forces from controller signals using artificial neural networks
Autorzy:
Bugdayci, Nevzat Bircan
Wegener, Konrad
Postel, Martin
Powiązania:
https://bibliotekanauki.pl/articles/2171771.pdf
Data publikacji:
2022
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
milling
cutting force monitoring
artificial neural network
Opis:
A new approach is presented to monitor the average cutting forces that are used for the calculation of the average cutting coefficients through neural networks using available controller signals. The cutting forces and the relevant controller signals are measured using a dynamometer and commercially available software supplied by the controller manufacturer in the calibration stage. Then a neural network is trained, which treats these controller signals as inputs and the cutting forces as the outputs. Finally, the average cutting forces for a new milling operation are predicted using the trained neural network without using a dynamometer. The proposed approach is validated using an experimental study, where a good match between predictions and measured forces is achieved. It is also shown that cutting coefficients can be calibrated and stability lobe diagrams can be generated using this method.
Źródło:
Journal of Machine Engineering; 2022, 22, 4; 54--70
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Preface to special issue on Modern Intelligent Systems Concepts II
Autorzy:
Idrissi, Abdellah
Powiązania:
https://bibliotekanauki.pl/articles/2141893.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
modern intelligent systems
artificial neural network
ANN
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 4; 35-36
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Interaktywny system edukacyjny wprowadzający w zagadnienie sztucznych sieci neuronowych
Interactive educational system introducing into issue of artificial neural networks
Autorzy:
Olszewski, T.
Boniecki, P.
Weres, J.
Powiązania:
https://bibliotekanauki.pl/articles/287816.pdf
Data publikacji:
2005
Wydawca:
Polskie Towarzystwo Inżynierii Rolniczej
Tematy:
sztuczna sieć neuronowa
edukacyjny system informatyczny
modelowanie neuronowe
sztuczna inteligencja
artificial neural network
educational computer system
artificial intelligence
Opis:
Dziedzina sztucznych sieci neuronowych ma swoje źródło w badaniach dotyczących sztucznej inteligencji. Stanowią one próbę naśladowania najważniejszych cech charakteryzujących biologiczne systemy nerwowe. Nazwą „sztuczne sieci neuronowe” (SSN) określa się dziś najczęściej symulatory programowe, umożliwiające modelowanie sieci na komputerach klasy PC. Sztuczne sieci neuronowe pozwalają na modelowanie systemów empirycznych o nieokreślonych zależnościach, trudnych do opisania tradycyjnymi, deterministycznymi metodami. Mają również zdolność generalizacji i uogólniania. Dzięki swym cechom SSN znajdują zastosowanie w rozwiązywaniu różnych problemów w wielu, niepowiązanych z sobą dziedzinach, jak: finanse, medycyna czy inżynieria rolnicza. Celowe jest więc wykonanie informatycznego systemu edukacyjnego, który pozwoli w łatwy i przystępny sposób zapoznać użytkownika z tematyką modelowania neuronowego.
The domain of artificial neural networks has its own source in the research of artificial intelligence. Artificial neural networks (ANN) are trying to imitate the most important features which represent the biological nervous systems. Nowadays in most cases the name of “artificial neural networks” define as programming simulators which allows the modeling of networks on PC computers. ANN permits to modeling empirical systems which have indefinable relationships and are hard to present in a traditional deterministic methods. They have as well the ability to generalize. Owing to its features, ANN applies in resolving variety of problems in many totally different areas, like: finances, medicine or agricultural engineering. It is purposeful to prepare educational informatics system which allows a user to get closer to subjects of neural modeling in easy and accessible way.
Źródło:
Inżynieria Rolnicza; 2005, R. 9, nr 8, 8; 293-298
1429-7264
Pojawia się w:
Inżynieria Rolnicza
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 309

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