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Wyniki wyszukiwania dla: ARTIFICIAL INTELLIGEMNCE
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Waldemar Korłub dr inż.
OsobyWaldemar Korłub uzyskał tytuł inżyniera w 2011 roku, tytuł magistra w 2012 roku oraz stopień doktora w dyscyplinie informatyki w 2017 roku na Wydziale Elektroniki Telekomunikacji i Informatyki Politechniki Gdańskiej. Jego zainteresowania naukowe obejmują: systemy rozproszone ze szczególnym uwzględnieniem systemów typu grid i chmur obliczeniowych, systemy autonomiczne zdolne do samodzielnej optymalizacji, zarządzania zasobami, ochrony...
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Hybrid System for Ship-Aided Design Automation
PublikacjaA 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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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublikacjaThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Analysis of the Degradation Process of Alginate-Based Hydrogels in Artificial Urine for Use as a Bioresorbable Material in the Treatment of Urethral Injuries
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublikacjaThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublikacjaLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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International Journal of Swarm Intelligence Research
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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE RESEARCH
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International Journal of Computational Intelligence and Applications
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International Journal of Ambient Computing and Intelligence
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International Journal of Computational Intelligence Techniques
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Applied Computational Intelligence and Soft Computing
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Journal of Policing, Intelligence and Counter Terrorism
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International Journal of Computational Intelligence Systems
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International Journal of Computational Intelligence in Control
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International Journal of Advanced Intelligence Paradigms
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International Journal of Technology Intelligence and Planning
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Communicable diseases intelligence quarterly report
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International Journal of Business Intelligence Research
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Idea zastosowania sztucznej inteligencji w prognozowaniu wpływu drgań komunikacyjnych na odpowiedź dynamiczną budynków mieszkalnych
PublikacjaW poniższym artykule autorzy analizują wpływ drgań komunikacyjnych na budynki mieszkalne oraz metodykę pomiarową według PN-85 B-02170 [1]. Problemem badawczym jest opracowanie prostej metody prognozowania wpływu drgań na budynki mieszkalne w taki sposób, aby nie było konieczne przeprowadzanie pracochłonnych i kosztownych pomiarów polowych. W tym celu wykonano analizę przy użyciu algorytmów opartych na sztucznej inteligencji oraz...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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Artificial neural networks as a tool for selecting the parameters of prototypical under sleeper pads produced from recycled rubber granulate
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublikacjaBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublikacjaPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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European Conference on Artificial Intelligence
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Artificial Intelligence and Applications Conference
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Artificial Intelligence Applications and Innovations
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Artificial Intelligence in Medicine in Europe
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Artificial Intelligence in Knowledge Management
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Advanced Course on Artificial Intelligence
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Conference on Artificial Intelligence for Applications
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International Conference on Artificial Intelligence
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Argentine Symposium on Artificial Intelligence
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Conference in Uncertainty in Artificial Intelligence
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Portuguese Conference on Artificial Intelligence
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Tomasz Menet mgr inż.
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Cognitive motivations and foundations for building intelligent decision-making systems
PublikacjaConcepts based on psychology fit well with current research trends related to robotics and artificial intelligence. Biology-inspired cognitive architectures are extremely useful in building agents and robots, and this is one of the most important challenges of modern science. Therefore, the widely viewed and far-reaching goal of systems research and engineering is virtual agents and autonomous robots that mimic human behavior in...
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Deep learning in the fog
PublikacjaIn 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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Optymalizacja treningu i wnioskowania sieci neuronowych
PublikacjaSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Artificial neural network model of hardness, porosity and cavitation erosion wear of APS deposited Al2O3 -13 wt% TiO2 coatings
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Dynamic electrochemical impedance spectroscopy and polarization studies to evaluate the inhibition effect of benzotriazole on copper-manganese-aluminium alloy in artificial seawater
PublikacjaPrzeprowadzono badania wpływu benzotriazolu (BTA) na korozję nowego typ mosiądzu (CMA) w środowisku syntetycznej wody morskiej przy użyciu dynamicznej elektrochemicznej spektroskopii impedancyjnej (DEIS), techniki polaryzacji rezystancyjnej i ekstrapolacji krzywych Tafela. Wyniki pomiarowe otrzymane przy użyciu tych metod wskazują spadek szybkości korozji wraz ze wzrostem stężenia BTA. Wskazuje to na inhibicyjne własności BTA w...
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Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
PublikacjaIn an electric vehicle (EV), using more than one energy source often provides a safe ride without concerns about range. EVs are powered by photovoltaic (PV), battery, and ultracapacitor (UC) systems. The overall results of this arrangement are an increase in travel distance; a reduction in battery size; improved reaction, especially under overload; and an extension of battery life. Improved results allow the energy to be used efficiently,...
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Effect of Melanin on the Stability of Casein Films Exposed to Artificially Accelerated UV Aging
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Emotions Embodied in the SVC of an Autonomous Driver System
PublikacjaA concept of embodied intelligence (EI) is considered. None of such implementations can be fully identified with artificial intelligence. Projects that dare to approach AI and EI should be based on both the AI concepts (symbolic and sub-symbolic), in solving real problems of perception and decision-making. Therefore, the EI, in this paper, is understood as a methodology that uses all available resources and algorithms from the...
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Wykorzystanie sztucznych sieci neuronowych do szacowania wpływu drgań na budynki jednorodzinne
PublikacjaW artykule przedstawiono metodę prognozowania wpływu drgań na budynki mieszkalne z wykorzystaniem sztucznych sieci neuronowych. Drgania komunikacyjne mogą doprowadzić do uszkodzenia elementów konstrukcyjnych, a nawet do awarii budynku. Najczęstszym efektem są jednak rysy, pękanie tynku i wypraw. Metody oparte na sztucznej inteligencji są przybliżone, ale stanowią wystarczająco dokładną i ekonomiczną alternatywę dla tradycyjnych...