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Tytuł:
Neural modeling and optimization of the coverage of the sprayed surface
Autorzy:
Cieniawska, B.
Pentoś, K.
Łuczycka, D.
Powiązania:
https://bibliotekanauki.pl/articles/200585.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
spray nozzle
spraying efficiency
spray coverage
artificial neural network
genetic algorithm
Opis:
Improving application efficiency is crucial for both the economic and environmental aspects of plant protection. Mathematical models can help in understanding the relationships between spray application parameters and efficiency, and reducing the negative impact on the environment. The effect of nozzle type, spray pressure, driving speed and spray angle on spray coverage on an artificial plant was studied. Artificial intelligence techniques were used for modeling and the optimization of application process efficiency. The experiments showed a significant effect of droplet size on the percent area coverage of the sprayed surfaces. A high value of the vertical transverse approach surface coverage results from coarse droplets, high driving speed, and nozzles angled forward. Increasing the vertical transverse leaving surface coverage, as well as the coverage of the sum of all sprayed surfaces, requires fine droplets, low driving speed, and nozzles angled backwards. The maximum coverage of the upper level surface is obtained with coarse droplets, low driving speed, and a spray angle perpendicular to the direction of movement. The choice of appropriate nozzle type and spray pressure is an important aspect of chemical crop protection. Higher upper level surface coverage is obtained when single flat fan nozzles are used, while twin nozzles produce better coverage of vertical surfaces. Adequate neural models and evolutionary algorithms can be used for pesticide application process efficiency optimization.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 3; 601-608
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial neural networks in mechanical surface enhancement technique for the prediction of surface roughness and microhardness of magnesium alloy
Autorzy:
Cagan, S. C.
Maci, M.
Buldum, M. M.
Maci, C.
Powiązania:
https://bibliotekanauki.pl/articles/201157.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial neural network
prediction
ball burnishing
magnesium alloys
AZ91D
Opis:
The artificial neural network method (ANN) is widely used in both modeling and optimization of manufacturing processes. Determination of optimum processing parameters plays a key role as far as both cost and time are concerned within the manufacturing sector. The burnishing process is simple, easy and cost-effective, and thus it is more common to replace other surface finishing processes in the manufacturing sector. This study investigates the effect of burnishing parameters such as the number of passes, burnishing force, burnishing speed and feed rate on the surface roughness and microhardness of an AZ91D magnesium alloy using different artificial neural network models (i.e. the function fitting neural network (FITNET), generalized regression neural network (GRNN), cascade-forward neural network (CFNN) and feed-forward neural network (FFNN). A total of 1440 different estimates were made by means of ANN methods using different parameters. The best average performance results for surface roughness and microhardness are obtained by the FITNET model (i.e. mean square error (MSE): 0.00060608, mean absolute error (MAE): 0.01556013, multiple correlation coefficient (R): 0.99944545), using the Bayesian regularization process (trainbr)). The FITNET model is followed by the FFNN (i.e. MAE: 0.01707086, MSE: 0.00072907, R: 0.99932069) and CFNN (i.e. MAE: 0.01759166, MSE: 0.00080154, R: 0.99924845) models with very small differences, respectively. The GRNN model has noted worse estimation results (i.e. MSE: 0.00198232, MAE: 0.02973829, R: 0.99900783) as compared with the other models. As a result, MSE, MAE and R values show that it is possible to predict the surface roughness and microhardness results of the burnishing process with high accuracy using ANN models.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 4; 729-739
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of evolutionary algorithm to design minimal phase digital filters with non-standard amplitude characteristics and finite bit word length
Autorzy:
Słowik, A.
Powiązania:
https://bibliotekanauki.pl/articles/202324.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
evolutionary algorithms
digital filters
minimal phase
finite bits word length
Opis:
In this paper an application of evolutionary algorithm to design minimal phase digital filters with non-standard amplitude characteristics and with finite bit word length is presented. Four digital filters with infinite impulse response were designed using the proposed method. These digital filters possess: linearly falling characteristics, linearly growing characteristics, nonlinearly falling characteristics, and nonlinearly growing characteristics, and they are designed using bit words with an assumed length. This bit word length is connected with a processing register size. This register size depends on hardware possibilities where digital filter is to be implemented. In this paper, a modification of the mutation operator is introduced too. Due to this modification, better results were obtained in relation to the results obtained using the evolutionary algorithm with other mutation operators. The digital filters designed using the proposed method can be directly implemented in the hardware (DSP system) without any additional modifications.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2011, 59, 2; 125-135
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
PCA-based approximation of a class of distributed parameter systems: classical vs. neural network approach
Autorzy:
Bartecki, K.
Powiązania:
https://bibliotekanauki.pl/articles/201641.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
distributed parameter system
principal component analysis
artificial neural network
supervised learning
unsupervised learning
Opis:
In this article, an approximation of the spatiotemporal response of a distributed parameter system (DPS) with the use of the principal component analysis (PCA) is considered. Based on a data obtained by the numerical solution of a set of partial differential equations, a PCA-based approximation procedure is performed. It consists in the projection of the original data into the subspace spanned by the eigenvectors of the data covariance matrix, corresponding to its highest eigenvalues. The presented approach is carried out using both the classical PCA method as well as two different neural network structures: two-layer feed-forward network with supervised learning (FF-PCA) and single-layer network with unsupervised, generalized Hebbian learning rule (GHA-PCA). In each case considered, the effect of the approximation model structure represented by the number of eigenvectors (or, in the neural case, units in the network projection layer) on the mean square approximation error of the spatiotemporal response and on the data compression ratio is analysed. As shown in the paper, the best approximation quality is obtained for the classical PCA method as well as for the FF-PCA neural approach. On the other hand, an adaptive learning method for the GHA-PCA network allows to use it in e.g. an on-line identification scheme.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 651-660
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial bee colony based state feedback position controller for PMSM servo-drive – the efficiency analysis
Autorzy:
Tarczewski, T.
Niewiara, L. J.
Grzesiak, L. M.
Powiązania:
https://bibliotekanauki.pl/articles/200239.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
tuning
PMSM servo-drive
artificial bee colony algorithm
linear-quadratic optimization problem
pole placement
Opis:
This paper presents a state feedback controller (SFC) for position control of PMSM servo-drive. Firstly, a short review of the commonly used swarm-based optimization algorithms for tuning of SFC is presented. Then designing process of current control loop as well as of SFC with feedforward path is depicted. Next, coefficients of controller are tuned by using an artificial bee colony (ABC) optimization algorithm. Three of the most commonly applied tuning methods (i.e. linear-quadratic optimization, pole placement technique and direct selection of coefficients) are used and investigated in terms of positioning performance, disturbance compensation and robustness against plant parameter changes. Simulation analysis is supported by experimental tests conducted on laboratory stand with modern PMSM servo-drive.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 5; 997-1007
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Trajectory tracking and collision avoidance for the formation of two-wheeled mobile robots
Autorzy:
Kowalczyk, W.
Kozłowski, K.
Powiązania:
https://bibliotekanauki.pl/articles/200897.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
robot formation
nonholonomic robot
stability analysis
Lyapunov-like function
path following
artificial potential function
Opis:
This paper presents control method for multiple two-wheeled mobile robots moving in formation. Trajectory tracking algorithm from [7] is extended by collision avoidance, and is applied to the different type of formation task: each robot in the formation mimics motion of the virtual leader with a certain displacement. Each robot avoids collisions with other robots and circular shaped, static obstacles existing in the environment. Artificial potential functions are used to generate repulsive component of the control. Stability analysis of the closed-loop system is based on Lyapunov-like function. Effectiveness of the proposed algorithm is illustrated by simulation results.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 5; 915-924
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Early detection of major diseases in turmeric plant using improved deep learning algorithm
Autorzy:
Devisurya, V.
Devi Priya, R.
Anitha, N.
Powiązania:
https://bibliotekanauki.pl/articles/2173642.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
computer vision
turmeric leaf diseases detection
sztuczna inteligencja
wizja komputerowa
wykrywanie chorób liści kurkumy
Opis:
Turmeric is affected by various diseases during its growth process. Not finding its diseases at early stages may lead to a loss in production and even crop failure. The most important thing is to accurately identify diseases of the turmeric plant. Instead of using multiple steps such as image pre-processing, feature extraction, and feature classification in the conventional method, the single-phase detection model is adopted to simplify recognizing turmeric plant leaf diseases. To enhance the detection accuracy of turmeric diseases, a deep learning-based technique called the Improved YOLOV3-Tiny model is proposed. To improve detection accuracy than YOLOV3-tiny, this method uses residual network structure based on the convolutional neural network in particular layers. The results show that the detection accuracy is improved in the proposed model compared to the YOLOV3-Tiny model. It enables anyone to perform fast and accurate turmeric leaf diseases detection. In this paper, major turmeric diseases like leaf spot, leaf blotch, and rhizome rot are identified using the Improved YOLOV3-Tiny algorithm. Training and testing images are captured during both day and night and compared with various YOLO methods and Faster R-CNN with the VGG16 model. Moreover, the experimental results show that the Cycle-GAN augmentation process on turmeric leaf dataset supports much for improving detection accuracy for smaller datasets and the proposed model has an advantage of high detection accuracy and fast recognition speed compared with existing traditional models.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 2; art. no. e140689
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial immune system in planning deliveries in a short time
Autorzy:
Mrówczyńska, B.
Król, A.
Czech, P.
Powiązania:
https://bibliotekanauki.pl/articles/200739.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial immune system
genetic algorithm
simulated annealing
open vehicle routing problem
on-time delivery
Taguchi method
Opis:
In the calculations presented in the article, an artificial immune system (AIS) was used to plan the routes of the fleet of delivery vehicles supplying food products to customers waiting for the delivery within a specified, short time, in such a manner so as to avoid delays and minimize the number of delivery vehicles. This type of task is classified as an open vehicle routing problem with time windows (OVRPWT). It comes down to the task of a traveling salesman, which belongs to NP-hard problems. The use of the AIS to solve this problem proved effective. The paper compares the results of AIS with two other varieties of artificial intelligence: genetic algorithms (GA) and simulated annealing (SA). The presented methods are controlled by sets of parameters, which were adjusted using the Taguchi method. Finally, the results were compared, which allowed for the evaluation of all these methods. The results obtained using AIS proved to be the best.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 5; 969-980
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Residual life estimation of fabricated humidity sensors using different artificial intelligence techniques
Autorzy:
Bhargava, C.
Aggarwal, J.
Sharma, P. K.
Powiązania:
https://bibliotekanauki.pl/articles/201564.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
composite material
artificial intelligence
humidity sensor
accelerated life testing
SEM
materiał kompozytowy
sztuczna inteligencja
czujnik wilgotności
Opis:
Background: a humidity sensor is used to sense and measure the relative humidity of air. A new composite system has been fabricated using environmental pollutants such as carbon black and low-cost zinc oxide, and it acts as a humidity sensor. Residual life of the sensor is calculated and an expert system is modelled. For properties and nature confirmation, characterization is performed, and a sensing material is fabricated. Methodology: characterization is performed on the fabricated material. Complex impedance spectroscopy (CIS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) are all used to confirm the surface roughness, its composite nature as well as the morphology of the composite. The residual lifetime of the fabricated humidity sensor is calculated by means of accelerated life testing. An intelligent model is designed using artificial intelligence techniques, including the artificial neural network (ANN), fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS). Results: maximum conductivity obtained is 6.4£10−3 S/cm when zinc oxide is doped with 80% of carbon black. Conclusion: the solid composite obtained possesses good humidity-sensing capability in the range of 30–95%. ANFIS exhibits the maximum prediction accuracy, with an error rate of just 1.1%.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 1; 147-154
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Type of modulation identification using Wavelet Transform and Neural Network
Autorzy:
Walenczykowska, M.
Kawalec, A.
Powiązania:
https://bibliotekanauki.pl/articles/201661.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
modulation identification
artificial neural networks
continuous wavelet transform (CWT)
identyfikacja modulacji
sztuczne sieci neuronowe (SSN)
transformacja falkowa (CWT)
Opis:
Automatic recognition of the signal modulation type turned out to be useful in many areas, including electronic warfare or surveillance. The wavelet transform is an effective way to extract signal features for identification purposes. In this paper there are M-ary ASK, M-ary PSK, M-ary FSK, M-ary QAM, OOK and MSK signals analysed. The mean value, variance and central moments up to five of continuous wavelet transform (CWT) are used as signal features. The principal component analysis (PCA) is applied to reduce a number of features. A multi-layer neural network trained with backpropagation learning algorithm is considered as a classifier. There are two research variants: interclass and intraclass recognition with a wide range of signal-to-noise ratio (SNR).
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2016, 64, 1; 257-261
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Assessment of wind energy resources using artificial neural networks – case study at Łódź Hills
Autorzy:
Korupczyński, R.
Trajer, J.
Powiązania:
https://bibliotekanauki.pl/articles/199792.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
wind speed
artificial neural network
wind resources
measure-correlate-predict
prędkość wiatru
sztuczna sieć neuronowa
zasoby wiatru
pomiar-korelacja-przewidywanie
Opis:
The aim of this paper is to answer the question: Are the Łódź Hills useful for electrical energy production from wind energy or not? Due to access to short-term data related to wind measurements (the period of 2008 and 2009) from a local meteorological station, the measure – correlate – predict approach have been applied. Long-term (1979‒2016) reference data were obtained from ECWMF ERA-40 Reanalysis. Artificial neural networks were used to calculate predicted wind speed. The obtained average wind speed and wind power density was 4.21 ms–1 and 70 Wm–1, respectively, at 10 m above ground level (5.51 ms–1, 170 Wm–1 at 50 m). From the point of view of Polish wind conditions, Łódź Hills may be considered useful for wind power engineering.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 1; 115-124
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent system supporting technological process planning for machining and 3D printing
Autorzy:
Rojek, Izabela
Mikołajewski, Dariusz
Kotlarz, Piotr
Macko, Marek
Kopowski, Jakub
Powiązania:
https://bibliotekanauki.pl/articles/2090703.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
AI
intelligent system
technological process
machining
3D printing
sztuczna inteligencja
system inteligentny
proces technologiczny
obróbka skrawaniem
druk 3D
Opis:
The study aimed to develop a system supporting technological process planning for machining and 3D printing. Such a system should function similarly to the way human experts act in their fields of expertise and should be capable of gathering the necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods and their significant effectiveness in supporting technological process planning. The purpose of this article is to show an intelligent system that includes knowledge, models, and procedures supporting the company’s employees as part of machining and 3D printing. Few works are combining these two types of processing. Nowadays, however, these two types of processing overlap each other into a common concept of hybrid processing. Therefore, in the opinion of the authors, such a comprehensive system is necessary. The system-embedded knowledge takes the form of neural networks, decision trees, and facts. The system is presented using the example of a real enterprise. The intelligent expert system is intended for process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise and are not very familiar with its machinery and other means of production.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136722, 1--8
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent system supporting technological process planning for machining and 3D printing
Autorzy:
Rojek, Izabela
Mikołajewski, Dariusz
Kotlarz, Piotr
Macko, Marek
Kopowski, Jakub
Powiązania:
https://bibliotekanauki.pl/articles/2173593.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
AI
intelligent system
technological process
machining
3D printing
sztuczna inteligencja
system inteligentny
proces technologiczny
obróbka skrawaniem
druk 3D
Opis:
The study aimed to develop a system supporting technological process planning for machining and 3D printing. Such a system should function similarly to the way human experts act in their fields of expertise and should be capable of gathering the necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods and their significant effectiveness in supporting technological process planning. The purpose of this article is to show an intelligent system that includes knowledge, models, and procedures supporting the company’s employees as part of machining and 3D printing. Few works are combining these two types of processing. Nowadays, however, these two types of processing overlap each other into a common concept of hybrid processing. Therefore, in the opinion of the authors, such a comprehensive system is necessary. The system-embedded knowledge takes the form of neural networks, decision trees, and facts. The system is presented using the example of a real enterprise. The intelligent expert system is intended for process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise and are not very familiar with its machinery and other means of production.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; art. no. e136722
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of residential lighting in Poland: results from a winter term survey
Autorzy:
Pracki, Piotr
Aslanoglu, Rengin
Kazak, Jan K.
Ulusoy, Begüm
Yekanialibeiglou, Sepideh
Powiązania:
https://bibliotekanauki.pl/articles/2173716.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
lighting technology
interior lighting
residential lighting
daylighting
artificial lighting
survey
technologia oświetleniowa
oświetlenie wewnętrzne
oświetlenie mieszkań
światło dzienne
oświetlenie sztuczne
badania ankietowe
Opis:
In 2020, an international project on residential lighting started and was implemented in four countries (Poland, Sweden, UK and Turkey). This article presents the results of a survey carried out in Poland, in the winter term between November 2020 and January 2021. A total of 125 Polish residents (59 women, 65 men, one person did not wish to specify gender) participated in the survey. A variety of data was collected on the respondents and their assessments as well as on their satisfaction with day- and artificial lighting in residential living spaces. The results from questionnaires were analyzed with STATISTICA 13.3. Descriptive statistics and Spearman rank order correlations were adopted to identify the light-related aspects, lighting patterns, and respondents’ perception of day- and artificial lighting conditions in living areas. The results revealed that satisfaction with daylighting in the living area, both in summer and winter, was significantly correlated with daylighting level, daylighting uniformity, sunlight exposure and view-out. The results also revealed that satisfaction with artificial lighting was significantly correlated with artificial lighting level, artificial lighting uniformity and color rendering. The results provide valuable information on lighting and factors that influence the luminous environment in residential living spaces.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143107
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modern methods in the field of machine modelling and simulation as a research and practical issue related to Industry 4.0
Autorzy:
Rojek, Izabela
Macko, Marek
Mikołajewski, Dariusz
Sága, Milan
Burczyński, Tadeusz
Powiązania:
https://bibliotekanauki.pl/articles/2086825.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Industry 4.0
Internet of Things
artificial intelligence
models
AI
simulation
IoT
Przemysł 4.0
internet rzeczy
internet przedmiotów
sztuczna inteligencja
modele
symulacja
Opis:
Artificial intelligence (AI) is changing many areas of technology in the public and private spheres, including the economy. This report reviews issues related to machine modelling and simulations concerning further development of mechanical devices and their control systems as part of novel projects under the Industry 4.0 paradigm. The challenges faced by the industry have generated novel technologies used in the construction of dynamic, intelligent, flexible and open applications, capable of working in real time environments. Thus, in an Industry 4.0 environment, the data generated by sensor networks requires AI/CI to apply close-to-real-time data analysis techniques. In this way industry can face both fresh opportunities and challenges, including predictive analysis using computer tools capable of detecting patterns in the data based on the same rules that can be used to formulate the prediction.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136717, 1--12
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
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