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Wyniki wyszukiwania dla: GLOBAL SENSITIVITY ANALYSIS · SURROGATE MODELING · NEURAL NETWORKS · SOBOL’ INDICES · TERMINATION CRITERIA
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Application of linear buckling sensitivity analysis to economic design of cylindrical steel silos composed of corrugated sheets and columns
PublikacjaThe paper deals with global stability of steel cylindrical silos composed of corrugated walls and vertical columns with loads imposed by a bulk solid following Eurocode 1. The optimum silo design with respect to the steel weight was based on a sensitivity analysis method. The changes of silo column profiles at each design step were performed by means of influence lines for the buckling load factor due to the unit column bending...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublikacjaSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Automatic singing quality recognition employing artificial neural networks
PublikacjaCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublikacjaWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublikacjaOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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Diagnosis of damages in family buildings using neural networks
PublikacjaThe article concerns a problem of damages in family buildings, which result from traffic-induced vibrations. These vibrations arise from various causes and their size is influenced by many factors. The most important is the type of a road, type and weight of vehicles that run on the road, type and condition of the road surface, the distance from the house to the source of vibrations and many others which should be taken into account....
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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublikacjaIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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An Analysis of Sustainability Reporting Practices of the Global Airline Industry
PublikacjaSustainability reporting (SR) has become a standard practice for many organisations worldwide. The purpose of this paper is to explore and develop our understanding of the global airline industry’s SR practices. Content analysis was employed to map which reporting frameworks the global commercial airline industry has recently used to report their non-financial impacts. Additionally, comparisons were made in the application of SR...
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Neural Networks and the Evolution of Environmental Change
PublikacjaZmiany środowiskowe na Ziemii są odwieczne i liczą około 4 miliardy lat. Homo sapiens wpłynął na każdy aspekt środowiska ziemskiego w wyniku rozwoju ludzkości na przestrzeni ostatnich milionów lat. Ale nic tak nie wpłynęło na wzrost i szybkość zmian na Ziemi jak ludzka aktywność w ciągu ostatnich dwóch stuleci. Po raz pierwszy zmiany ekosystemów były tak intensywne i zachodziły na tka wielką skalę i z taką szybkością jak nigdy...
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Artificial Neural Networks for Comparative Navigation
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks
PublikacjaArtykuł przedstawia metodę do wyznaczania charakterystyki pasożytniczych modulacji częstotliwości (kołysanie) obecnych w archiwalnych nagraniach dźwiękowych. Prezentowane podejście wykorzystuje śledzenie zmian sinusoidalnych komponentów dźwięku które odzwierciedlają przebieg kołysania. Analiza sinusoidalna wykorzystana jest do ekstrakcji składowych tonalnych ze zniekształconych nagrań dźwiękowych. Dodatkowo, w celu zwiększenia...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublikacjaPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Dynamic Bayesian Networks for Symbolic Polyphonic Pitch Modeling
PublikacjaSymbolic pitch modeling is a way of incorporating knowledge about relations between pitches into the process of an- alyzing musical information or signals. In this paper, we propose a family of probabilistic symbolic polyphonic pitch models, which account for both the “horizontal” and the “vertical” pitch struc- ture. These models are formulated as linear or log-linear interpo- lations of up to fi ve sub-models, each of which is...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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Towards bees detection on images: study of different color models for neural networks
PublikacjaThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Design and modeling of reliable networks
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Reliable Networks Design and Modeling
PublikacjaSłowo wstępne numeru specjalnego czasopisma Telecommunication Systems Journal
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Delamination Identification Using Global Convolution Networks
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublikacjaThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Efficient Surrogate Modeling and Design Optimization of Compact Integrated On-Chip Inductors Based on Multi-Fidelity EM Simulation Models
PublikacjaHigh-performance and small-size on-chip inductors play a critical role in contemporary radio-frequency integrated circuits. This work presents a reliable surrogate modeling technique combining low-fidelity EM simulation models, response surface approximations based on kriging interpolation, and space mapping technology. The reported method is useful for the development of broadband and highly accurate data-driven models of integrated...
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Functional safety in the context of risk appraisal criteria and cost-benefit analysis
PublikacjaRozdział przedstawia aktualne zagadnienia dotyczące analizy kosztów i efektów rozwiązań związanych z bezpieczeństwem na przykładzie systemów elektrycznych, elektronicznych i programowalnych elektronicznych (E/E/PE) pełniących funkcje sterowania i zabezpieczeń w obiektach podwyższonego ryzyka. Podkreśla się znaczenie kryteriów związanych z bezpieczeństwem, takich jak tolerowalność ryzyka (TOR) w kontekście analizy kosztów i efektów...
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Global value chains and labour markets – simultaneous analysis of wages and employment
PublikacjaThis study examines the overall effect of global value chains (GVCs) on wages and labour demand. It exploits the World Input–Output Database to measure GVC involvement via recently developed participation indices (using both backward and forward linkages) and the relative GVC position using three-stage least squares regression. We find that the relative GVC position is negatively correlated with wages and employment and that the...
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Probabilistic Analysis of Structure Models using Target Random Sampling (TRS)
PublikacjaThe work presents testing methods of sensitivity and reliability of mechanical or structural systems. All computations concerned the case of Zigler column, a simple model of a compressed column involving two random variables only. A conclusion was drawn that the standard Monte Carlo method, its reduction variants and the response surface method allow to assess the sensitivity of structural response to the variation of random structural...
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Modeling of the fascia-mesh system and sensitivity analysis of a junction force after a laparoscopic ventral hernia repair
PublikacjaW pracy rozpatrywano prosty model cięgnowy układu powięż-siatka do oszacowania siły połączenia siatki z powięzią po operacji laparoskopowej przepukliny brzusznej. Cięgno obciążone jest ciśnieniem wewnątrz brzusznym, symulującym kaszel, oraz przemieszczeniami jego końców wywołanymi skłonami pacjenta. Wpływ poszczególnych parametrów cięgna na siłę połączenia określono za pomocą analizy wrażliwości. Sformułowano pewne wnioski ważne...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublikacjaThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublikacjaEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Global value chains and productivity gains: a cross-country analysis
PublikacjaThe main aim of this article is to assess the implications of involvement in global value chains (GVC) on sectoral productivity growth from the international perspective. Our panel data analysis covers 40 countries, 20 industries (13 manufacturing and 7 services sectors) in the period 1995–2011. Estimation results suggest that there is a positive link between TFP growth and the involvement of sectors in global value chains (measured...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublikacjaA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublikacjaIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...
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Study on surface termination of boron-doped diamond electrodes under anodic polarization in H2SO4 by means of dynamic impedance technique
PublikacjaAnodic oxidation is a popular way to modify termination bonds at boron doped diamond electrodes altering their electrochemical and physicochemical properties. Our studies, performed with dynamic electrochemical impedance spectroscopy technique, supported with X-ray photoelectron spectroscopy and ellipsometry analysis prove its utility in continuous on-line monitoring of impedance changes on the electrode surface under polarization...
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublikacjaMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Reliable low-cost surrogate modeling and design optimisation of antennas using implicit space mapping with substrate segmentation
PublikacjaAbstract: In this work, a reliable methodology for fast simulation-driven design optimisation of antenna structures is proposed. The authors’ approach exploits implicit space mapping (ISM) technology. To adopt it for handling antenna structures, they introduce substrate segmentation with separate dielectric permittivity value assigned for each segment as ISM preassigned parameters. At the same time, the coarse model for space mapping...
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SENSITIVITY ANALYSIS IN THE REHABILITATION OF HISTORIC TIMBER STRUCTURES ON THE EXAMPLES OF GREEK CATHOLIC CHURCHES IN POLISH SUBCARPATHIA
PublikacjaThis work concerns structural and sensitivity analysis of carpentry joints used in historic wooden buildings in south-eastern Poland and western Ukraine. These are primarily sacred buildings and the types of joints characteristic for this region are saddle notch and dovetail joints. Thus, in the study the authors focus on these types of corner log joints. Numerical models of the joints are defined and finite element simulations...
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Electrodes array for contactless ECG measurement of a bathing person - a sensitivity analysis
PublikacjaAn applicability of a remote (contactless) electrocardiogram (ECG) measurements in a bathtub is presented in the paper. Possibility of ECG measurements in shallowly filled tube with a water was examined. A bathing person was, both, sitting and lying during experiments performed. The problem became non-trivial when the bathing person was moving in reference to a fixed set of electrodes and located at the longer walls of the bathtub....
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Multiparameter sensitivity analysis of a GFRP composite footbridge of a sandwich structure and U-shaped cross-section
PublikacjaThe paper deals with multiparameter sensitivity analysis of a composite footbridge. A shell‐like structure is 14.5 m long shows U‐shaped cross‐section and inner service dimensions 1.3 × 2.5 m. Glass fiber reinforced polymer GFRP laminate constitutes faces of a sandwich structure while PET foam received from recycled bottle builts a core. The structure was divided into 285 independent areas where the thickness of laminates and stiffness...
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Analysis of the Multiple Attribute Decision Making Problem with Incomplete Information about Preferences among the Criteria
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Sensitivity analysis of free torsional vibration frequencies of thin-walled laminated beams under axial load
PublikacjaThe paper addresses sensitivity analysis of free torsional vibration frequencies of thin-walled beams of bisymmetric open cross-section made of unidirectional fibre-reinforced laminate. The warping effect and the axial end load are taken into account. The consideration is based upon the classical theory of thin-walled beams of non-deformable cross-section. The first-order sensitivity variation of the frequencies is derived with...
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New Performance Indices for Power System Stabilizers
PublikacjaThe subject of the article is issues related to innovative indices for power system stabilizers (PSSs). These new indices will be able to quickly show which PSS (among many other PSSs) is not working properly and that advanced optimization and simulation methods should be used to improve the PSS settings. The authors note the fact that the acceptance requirements for PSSs are different in various power systems. Moreover, the authors...
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublikacjaThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Neural networks in the diagnostics of induction motor rotor cages.
PublikacjaW środowisku Lab VIEW została stworzona aplikacja służąca do pomiaru, prezentacji i zapisu przebiegów widma prądu stojana z uwzględnieniem potrzeb pomiarowych występujących podczas badania wirników silników indukcyjnych przy użyciu sieci neuronowych. Utworzona na bazie zbioru uczącego sieć Kohonena z powodzeniem rozwiązała stawiany przed nią problem klasyfikacji widm prądu stojana, a co za tym idzie również diagnozy stanu...
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Applications of neural networks and perceptual masking to audio restoration
PublikacjaOmówiono zastosowania algorytmów uczących się w dziedzinie rekonstruowania nagrań fonicznych. Szczególną uwagę zwrócono na zastosowanie sztucznych sieci neuronowych do usuwania zakłócających impulsów. Ponadto opisano zastosowanie inteligentnego algorytmu decyzyjnego do sterowania maskowaniem perceptualnym w celu redukowania szumu.
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Application of neural networks for turbine rotor trajectory investigation.
PublikacjaW pracy przedstawiono rezultaty badań sieci neuronowych przewidujących trajektorię wirnika turbinowego uzyskanych ze stanowiska turbiny modelowej. Badania wykazały, iż sieci neuronowe wydają się być z powodzeniem zastosowane do przewidywania trajektorii ruchu wirnika turbiny. Najważniejszym zadaniem wydaje się poprawne określenie wektorów sygnałów wejściowych oraz wyjściowych jak również prawidłowe stworzenie sieci neuronowej....
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Basic sensitivity analysis of a telecommunication tower complementing standard reinforcement design process
PublikacjaThis paper presents straightforward sensitivity assessment of a telecommunication tower. The analysis is set toidentify the elements of the tower which may be reinforced with the greatest structural advantage. As current expertopin ions on structural redesign of similar structures due to a planned addition of extra loads are mainly based ondeterministic computations or engineering intuition,...
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Probabilistic sensitivity of limit states of structures. The Monte Carlo simulation
PublikacjaDesign sensitivity deals with the variation of structural response, implicitly dependent on the design variables of the problem. An attempt is made to implement probabilistic notation in engineering sensitivity analysis. The procedure to implement the sensitivity of a structural limit state to a given basic variable is described in the paper - its main idea, depicted by a flowchart and numerical examples of engineering analysis....