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Search results for: sztuczna inteligencja
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Optimalization of TiO2 nanotube geometry using fuzzy reasoning approach
PublicationThe geometry of TiO2 nanotube layer on titanium, obtained by electrochemical anodization, has been determined by using fuzzy reasoning approach. A proposed method showed the possibility of nanotube array architecture optimization by choosing an appropriate anodization condition. A fuzzy logic controller (FLC) was utilized using Matlab Software.
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Evolutionary Algorithms in MPLS network designing
PublicationMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review
PublicationComputer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...
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Hybrid System for Ship-Aided Design Automation
PublicationA hybrid support system for ship design based on the methodology of CBR with some artificial intelligence tools such as expert system Exsys Developer along with fuzzy logic, relational Access database and artificial neural network with backward propagation of errors.
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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Optimization of Self-Organized TiO2 Nanotube Geometry on Ti and Ti Alloys Using Fuzzy Logic Reasoning
PublicationThe geometry of self-organized TiO2 nanotubes, obtained by electrochemicalanodization, has been determined by using fuzzy reasoning approach. The efficiency of TiO2nanotubular layer in biomedical applications depends on geometry and available surface area ofnanotubes, which can be determined by their diameter and length. The structure of nanotubesdepends on processing parameters of electrochemical anodization, like applied potential,anodization...
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Comparison of selected electroencephalographic signal classification methods
PublicationA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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Zastosowanie reguł rozmytych w komputerowej animacji postaci
PublicationPrzedmiotem badawczym rozprawy jest wykazanie możliwości wspomagania komputerowej animacji postaci poprzez wykorzystanie metod inteligentnych, szczególnie logiki rozmytej, w taki sposób, aby możliwe było uzyskiwanie animacji płynnych i nacechowanych stylistycznie, dla których punktem wyjścia są animacje schematyczne, które nie posiadają tych cech. Wiedza zawarta w literaturze animacji i wiedza oparta na wynikach wydobywania danych...
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Turbine stage design aided by artificial intelligence methods
PublicationZaproponowano ogólny, wydajny system wspomagania projektowania palisad , stopni i grupy stopni turbinowych. Zastosowane algorytmy wykorzystują algorytmy genetyczne, sieci neuronowe i obliczenia równoległe. Uzyskane rozwiązania projektowe są wysoko zoptymalizowane pod względem sprawności, a czas ich uzyskania jest o kilka rzędów wielkości mniejszy, niż przy zastosowaniu obliczeń CFD.
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Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublicationIn this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.
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Fuzzy logic gain scheduling for non - linear servo tracking
PublicationArtykuł zawiera propozycję strojenia jako metodę sterowania serwomechanizmem z silnie nieliniowymi elementami. Serwomechanizm steruje dwoma elementami układu śledzącego zamontowanymi na okręcie znajdującym się w morzu. W układzie występuje tarcie spoczynkowe przy zerowej prędkości oraz nieliniowe tarcie przeciwdziałające ruchowi w każdej z osi układu śledzącego. Zastosowany został podwójny układ sterowania ze sprzężeniem zwrotnym....
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublicationIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Deep learning in the fog
PublicationIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Efficiency comparison of selected endoscopic video analysis algorithms
PublicationIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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On a Method of Efficiency Increasing in Kaplan Turbine
PublicationThis paper presents a method of increasing efficiency in Kaplan-type turbine. The method is based on blade profile optimisation together with modelling the interaction between rotor and stator blades. Loss coefficient was chosen as the optimisation criterion, which is related directly to efficiency. Global optimum was found by means of Genetic Algorithms, and Artificial Neural Networks were utilised for approximations to reduce...
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublicationFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
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A Method for Optimising the Blade Profile in Kaplan Turbine
PublicationThis paper introduces a method of blade profile optimisation for Kaplan-type turbines, based on modelling the interaction between rotor and stator blades. Rotor and stator blade geometry is described mathematically by means of a midline curve and thickness distribution. Genetic algorithms are then used to find a global optimum that minimises the loss coefficient. This allows for variety of possible blade shapes and configurations....
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Review of the Complexity of Managing Big Data of the Internet of Things
PublicationTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublicationResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Artificial intelligence for biomedical engineering of polysaccharides: A short overview.
PublicationThe advent of computer-aided concepts and cognitive algorithms, along with fuzzy sets and fuzzy logic thoughts, supported the idea of ‘making computers think like people’ (Lotfi A. Zadeh, IEEE Spectrum, 21 (26–32), 1984). Such a school of thought enabled the sophistication of mission-oriented...
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Inteligentne wspomaganie podejmowania decyzji z wykorzystaniem metod sztucznej inteligencji w środowisku obliczeniowym typu grid
PublicationPodejmowanie decyzji jest uważane za jedno z najbardziej krytycznych działań w organizacji. W celu wsparcia tego złożonego procesu dla osób odpowiedzialnych różne niezależne, samodzielne systemy wspomagania decyzji zostały opracowane głównie w ostatnich dwóch dekadach. Patrząc w sposób komplementarny na te systemy, wiążemy je z rolą i funkcją, którą musi spełniać z punktu widzenia użytkownika. W rozdziale opisano systemy wspomagania...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Rozpoznawanie obiektów przez głębokie sieci neuronowe
PublicationW referacie zaprezentowane zostaną wyniki badań nad rozpoznawaniem obiektów w różnych warunkach za pomocą głębokich sieci neuronowych. Przeanalizowano działanie dwóch struktur – ResNet50 oraz VGG19. Systemy rozpoznawania obrazu wytrenowano oraz przetestowano na reprezentatywnej, bazie zawierającej 25 tys. zdjęć psów oraz kotów, która znacznie upraszcza analizowanie działania systemów ze względu na łatwość interpretacji zdjęć przez...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Parallelisation of genetic algorithms for solving university timetabling problems
PublicationAlgorytmy genetyczne stanowią ważną metodę rozwiązywania problemów optymalizacyjnych. W artykule skupiono się na projekcie równoległego algorytmu genetycznego pozwalającego uzyskiwać uniwersyteckie rozkłady zajęć, spełniające zarówno twarde jak i miękkie ograniczenia. Czytelnika wprowadzono w niektóre znane sposoby zrównoleglenia, przedstawiono również podejście autorów, ykorzystujące MPI. Przyjęto strukturę zarządzania opartą...
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Extinction Event Concepts for the Evolutionary Algorithms
PublicationThe main goal of this present paper is to propose a structure for a tool helping to determine how algorithm would react in a real live application, by checking it's adaptive capabilities in an extreme situation. Also a different idea of an additional genetic operator is being presented. As Genetic Algorithms are directly inspired by evolution, extinction events, which are elementary in our planet's development history, became...
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Musical phrase representation and recognition by means of neural networks and rough sets.
PublicationW artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych
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Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublicationThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublicationTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublicationCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
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Sztuczne sieci neuronowe modelem wczesnego ostrzegania
PublicationW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania zagrożenia upadłością polskich firm produkcyjnych.Głównym celem było porównanie skuteczności przewidywania zagrożeń upadłością polskich przedsiębiorstw przy pomocy modelu sztucznych sieci neuronowych i tradycyjnego modelu analizy dyskryminacyjnej.
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Zastosowanie sztucznych sieci neuronowych do prognozowania cen na Giełdzie Energii
PublicationOpisano narzędzie wykorzystujące sztuczne sieci neuronowe do prognozowania cen energii na giełdzie. Przedstawiono wyniki testowania modelu.
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Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Jak wykraść złoto smokowi? - uczenie ze wzmocnieniem w świecie Wumpusa
PublicationNiniejszy rozdział zawiera łagodne wprowadzenie do problematyki uczenia ze wzmocnieniem, w którym podstawy teoretyczne wyjaśniane są na przykładzie przewodnim, jakim jest zagadnienie nauczenia agenta poruszania się w świecie potwora o imieniu Wumpus (ang. Wumpus world), klasycznym środowisku do testowania logicznego rozumowania agentów (problem nietrywialny dla algorytmów uczenia ze wzmocnieniem). Przedstawiona jest główna idea...
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Inteligentne systemy agentowe w systemach zdalnego nauczania
PublicationW pracy omówiono inteligentne systemy agentowe w systemach zdalnego nauczania. Po krótkim przedstawieniu ewolucji systemów zdalnego nauczania i ich wybranych zastosowań, scharakteryzowano inteligentne agenty edukacyjne. Omówiono wykorzystanie programowania genetycznego oraz algorytmów neuro-ewolucyjnych do implementacji oprogramowania tej klasy. Ponadto, nawiązano do modelu Map-Reduce, który efektywnie wspiera architekturę nowoczesnego...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublicationLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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TECHNIK OCHRONY FIZYCZNEJ OSÓB I MIENIA JAKO ZAWÓD PRZYSZŁOŚCI
PublicationTechnik ochrony fizycznej osób i mienia jako zawód przyszłości Współczesne społeczeństwo coraz częściej stawia na bezpieczeństwo, zarówno w sektorze publicznym, jak i prywatnym. Rosnące zagrożenia, takie jak terroryzm, cyberprzestępczość, kradzieże czy akty wandalizmu, sprawiają, że zawód technika ochrony fizycznej osób i mienia staje się kluczowym elementem funkcjonowania nowoczesnych struktur społecznych i gospodarczych....
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublicationAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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Fuzzy Multi-Regional Fractional PID controller for Pressurized Water nuclear Reactor
PublicationThe paper presents the methodology for the synthesis of a Fuzzy Multi-Regional Fractional Order PID controller (FMR-FOPID) used to control the average thermal power of a PWR nuclear reactor in the load following mode. The controller utilizes a set of FOPID controllers and the fuzzy logic Takagi-Sugeno reasoning system. The proposed methodology is based on two optimization parts. The first part is devoted to finding the optimal...
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Data Reduction Algorithm for Machine Learning and Data Mining
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Prognozowanie wpływu drgań komunikacyjnych na budynki mieszkalne za pomocą sztucznych sieci neuronowych i maszyn wektorów wspierających
PublicationDrgania komunikacyjne mogą stanowić duże obciążenie eksploatacyjne budynku, powodując zarysowania i spękania tynków, odpadanie wypraw, zarysowania konstrukcji, pękanie elementów konstrukcji lub nawet zawalenie się budynku. Pomiary drgań na rzeczywistych konstrukcjach są pracochłonne i kosztowne, a co ważne nie w każdym przypadku są one uzasadnione. Celem pracy jest analiza autorskiego algorytmu, dzięki któremu z dużym prawdopodobieństwem...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublicationThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...