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Wyniki wyszukiwania dla: machine learning, music analysis, tonality
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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Self-Perceived Personal Brand Equity of Knowledge Workers by Gender in Light of Knowledge-Driven Organizational Culture: Evidence From Poland and the United States
PublikacjaThis study contributes to the limited literature on the personal branding of knowledge workers by revealing that a culture that incorporates knowledge, learning, and collaboration supports (explicit and tacit) knowledge sharing among employees and that sharing matters for knowledge workers’ self-perceived personal brand equity. Analysis of 2,168 cases from the United States and Poland using structural equation modeling (SEM) showed...
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Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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Broken rotor bar impact on sensorless control of induction machine
PublikacjaThe aim of the research is analysis of the sensorless control system of induction machine with broken rotor for diagnostic purposes. Increasing popularity of sensorless controlled variable speed drives requires research in area of reliability, range of stable operation, fault symptoms and application of diagnosis methods. T transformation (Cunha et al.,2003) used for conversion of instantaneous rotor currents electrical circuit...
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Bayesian Optimization for solving high-frequency passive component design problems
PublikacjaIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublikacjaThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublikacjaIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Computing methods for fast and precise body surface area estimation of selected body parts
PublikacjaCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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Analysis of Factors Influencing the Prices of Tourist Offers
PublikacjaTourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data...
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The KLC Cultures' Synergy Power, Trust, and Tacit Knowledge for Organizational Intelligence
PublikacjaThis paper examines the impact of knowledge, learning, and collaboration culturessynergy (the KLC approach) on organizational adaptability. The SEM analysis method was applied to verify the critical assumption of this paper: that the KLC approach and trust support knowledge-sharing processes (tacit and explicit) and are critical for organizational intelligence activation.Specifically, the empirical evidence, based on a 640-case...
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Deep neural networks for data analysis
Kursy OnlineThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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The KLC Cultures, Tacit Knowledge, and Trust Contribution to Organizational Intelligence Activation
PublikacjaIn this paper, the authors address a new approach to three organizational, functional cultures: knowledge culture, learning culture, and collaboration culture, named together the KLC cultures. Authors claim that the KLC approach in knowledge-driven organizations must be designed and nourished to leverage knowledge and intellectual capital. It is suggested that they are necessary for simultaneous implementation because no one of...
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Anna Czaja mgr inż.
OsobyPo ukończeniu studiów magisterskich na kierunku Informatyka (Politechnika Gdańska, Wydział Elektroniki, Telekomunikacji i Informatyki) przez szereg lat pracowała jako programista. Obecnie zatrudniona na stanowisku asystenta w Katedrze Zastosowań Informatyki w Zarządzaniu (Politechnika Gdańska, Wydział Zarządzania i Ekonomii). Uczestniczka studiów doktoranckich III stopnia na wydziale Zarządzania i Ekonomii na Politechnice Gdańskiej....
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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublikacjaThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublikacjaSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Feedback Control of Multiphase Induction Machines with Backstepping Technique
PublikacjaThe paper presents the control possibility of five phase induction machines. In the proposed solution the machine model vector form is not transformed to the (dq)-coordinate system, that is connected to rotor flux vector, but utilizes the stationary system ( αβ ). Moreover, the nonlinear model linearization is based on demonstrated nonlinear variables transformation for i-orthogonal ( αβ )(n) planes. By introducing the backstepping...
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Buzz-based honeybee colony fingerprint
PublikacjaNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublikacjaWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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Tomasz Edward Berezowski dr inż.
OsobyUrodził się w 1986 r. w Warszawie. Ukończył w 2009r. z wyróżnieniem Międzywydziałowe Studium Ochrony Środowiska SGGW w Warszawie, specjalność Restoration and Management of Environment. Doktorat obronił z wyróżnieniem na Vrije UIniversiteit Brussels w 2015 roku. W latach 2015-2017 pracował jako asystent, a następnie adiunkt na Wydziale Budownictwa i Inżynierii Środowiska SGGW. W roku 2017 został zatrudniony jako adiunkt na Wydziale...
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Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE)
Dane BadawczeHerbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE) is a research herbarium encompassing specimens of vascular plants and algae hosted by the Laboratory of Marine Plant Ecology at University of Gdańsk, Poland. The aim of Herbarium is to preserve marine plant and algae collections mostly from the Gulf of Gdańsk, but the herbarium...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublikacjaModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublikacjaFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Remote measurement of building usable floor area - Algorithms fusion
PublikacjaRapid changes that are taking place in the urban environment have significant impact on urban growth. Most cities and urban regions all over the world compete to increase resident and visitor satisfaction. The growing requirements and rapidity of introducing new technologies to all aspects of residents' lives force cities and urban regions to implement "smart cities" concepts in their activities. Real estate is one of the principal...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublikacjaPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublikacjaIn this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Technique for reducing erosion in large-scale circulating fluidized bed units
PublikacjaThis paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...
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Power Hardware-in-the-Loop Approach In Power System Development
PublikacjaThe main objective of the research is the verification of the Power Hardware-In-The-Loop (PHIL) approach in power system analysis and design. The premise of the article is that using PHIL approach the performance of the power system in steady and transient state conditions can be analysed in real power system conditions. Models of induction machine were developed and real time simulations were performed. Simulation variables were...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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The influence of brace to chord rotational connection stiffness on stability of the truss
PublikacjaThe paper is devoted to the numerical analysis of the roof truss subjected to upward wind loading and braced at the tensioned top chord. The linear buckling analysis were performed for the beam and shell model of the structure. As the result the influence of rotational connection stiffness between the brace and the top chord on the truss stability was appointed. The biaxial strength testing machine was used to conduct the experimental...
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Multimedia services applied to noise and hearing monitoring and measuring
PublikacjaThe goal of this chapter is to show a research study related to processing of data acquired by the multimedia services engineered at the multimedia systems department (MSD) of the Gdansk University of Technology. This concerns a survey on noise threat employing the multimedia noise monitoring system (MNMS) and hearing tests performed by the "I can hear. . . " system. The obtained results of the noise measurements revealed that...
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Comparative Study of Self-Organizing Maps vs. Subjective Evaluation of Quality of Allophone Pronunciation for Nonnative English Speakers
PublikacjaThe purpose of this study was to apply Self-Organizing Maps to differentiate between the correct and the incorrect allophone pronunciations and to compare the results with subjective evaluation. Recordings of a list of target words, containing selected allophones of English plosive consonants, the velar nasal and the lateral consonant, were made twice. First, the target words were read from the list by 9 non-native speakers and...
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THE METHODS OF TEACHING / LEARNING STRUCTURAL MECHANICS
PublikacjaStructural mechanics is a key issue to study for engineers. A high rank and high social responsibility profession requires both a high graded and intuitive approach. The evolution of learning / teaching methodology follows the novel technical achievements of every decade. The aim remains the same: to produce a professional to perform advanced relevant analysis and safe, optimal structural design
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublikacjaIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Online sound restoration system for digital library applications.
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Wpływ automatycznej kalibracji wizyjnego systemu pozycjonowania na dokładność lokalizacji elementu roboczego
PublikacjaW artykule przedstawiono strukturę i działanie automatycznego wizyjnego systemu pozycjonowania (PVS), który został zainstalowany na maszynie waterjet (WJ). Ponadto przeprowadzono analizę wpływu kalibracji na działanie PVS. Podstawę systemu stanowią dwie kamery internetowe zamontowane na przemysłowej maszynie WJ. W połączeniu z algorytmem identyfikacji, system przeznaczony jest do pozycjonowania WJ z dużą dokładnością. W tym celu...
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Analysis and evaluation of grouping methods for effective cutting tool operation
PublikacjaThis article presents the possibilities for using cluster analysis in the assignment of machine tools in automated manufacturing systems. Based on the similarity of manufacturing processes in the system, cutting tools have been grouped. The objective was to obtain groups of similar objects, which could potentially ensure the reduction of the frequency and time of setups, optimizing the maintenance of tool resources and improving...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublikacjaW 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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Development and performance analysis of a novel multiphase doubly-fed induction generator
PublikacjaThis paper presents the research into the design and performance analysis of a novel five-phase doubly-fed induction generator (DFIG). The designed DFIG is developed based on standard induction motor components and equipped with a five-phase rotor winding supplied from the five-phase inverter. This approach allows the machine to be both efficient and reliable due to the ability of the five-phase rotor winding to operate during...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublikacjaSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublikacjaFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Wybrane aspekty modelowania uderzenia pojazdem dźwigara wiaduktu
PublikacjaW pracy przedstawiono różne zagadnienia związane z uderzeniem pojazdu w dźwigar wiaduktu. Omówiono wybór modelu obliczeniowego, na podstawie porównania wyników dla modelu dźwigara zespolonego, modelu dźwigara stalowego oraz modelu wiaduktu. Następnie opisano model dźwigara zespolonego zastosowany w analizie MES oraz metodę wyznaczania współczynników tłumienia Rayleigha. Symulację numeryczną uderzenia dźwigara wiaduktu przez koparkę...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...