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Wyniki wyszukiwania dla: FIBER-REINFORCED CONCRETE BEAM, CHAINED MACHINE LEARNING MODEL, DUCTILITY INDEX, BENDING LOAD CAPACITY, ARTIFICIAL NEURAL NETWORKS
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn 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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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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Shear fracture of longitudinally reinforced concrete beams under bending using Digital Image Correlation and FE simulations with concrete micro-structure based on X-ray micro-computed tomography images
PublikacjaThe paper presents experimental and numerical investigations of the shear fracture in rectangular concrete beams longitudinally reinforced with steel or basalt bar under quasi-static three point bending. Shear fracture process zone formation and development on the surface of beams was investigated by Digital Image Correlation (DIC) whereas thorough analyses of 3D material micro-structure, air voids, width and curvature of shear...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublikacjaBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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Speech Analytics Based on Machine Learning
PublikacjaIn 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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Deep Learning Basics 2023/24
Kursy OnlineA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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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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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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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Acoustic emission signals in concrete beams under 3-point bending (polyolefin and steel fibre concrete)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of concrete beams with dimensions 40 x 40 x 160 cm3 under the 3-point bending. All specimens were manufactured based on the same concrete mixture composed of cement CEM I 42.5R (380 kg/m3), water (165 kg/m3), aggregate 0/2 mm (648 kg/m3), aggregate 2/8 mm (426 kg/m3), aggregate 8/16 mm (754...
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Artificial Neural Networks for Comparative Navigation
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublikacjaHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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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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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Complex Concrete Structures (CE) - 2021/2022
Kursy OnlineThe following issues in the field of concrete structures will be discussed in the lecture part: Mechanical properties of concrete and reinforcing steel; Calculation of reinforced concrete cross-sections bending; Calculation of reinforced concrete cross-sections shear; Serviceability limit state in reinforced concrete structures; Reinforced concrete slabs, one-way and cross-reinforced; Reinforced concrete stairs; Reinforced...
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Complex Concrete Structures (CE) - 2023/2024
Kursy OnlineThe following issues in the field of concrete structures will be discussed in the lecture part: Mechanical properties of concrete and reinforcing steel; Calculation of reinforced concrete cross-sections bending; Calculation of reinforced concrete cross-sections shear; Serviceability limit state in reinforced concrete structures; Reinforced concrete slabs, one-way and cross-reinforced; Reinforced concrete stairs; Reinforced...
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Analytical approach for membrane action in laterally-restrained reinforced concrete square slabs under uniformly distributed loads
PublikacjaLaterally-restrained reinforced concrete slabs can mobilise compressive membrane action and subsequent tensile membrane action under extreme loading conditions, thereby enhancing the load resistance under uniformly distributed loads. Previous analytical study focuses primarily on tensile membrane action in simply-supported slabs. This paper describes an analytical approach for membrane action in laterally-restrained square slabs....
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The method of analysis of damage reinforced concrete beams using terrestial laser scanning
PublikacjaThe authors present an analysis of the possibility to assess deformations and mechanisms of destructing bent reinforced concrete beams using the terrestrial laser scanning. As part of the experiments carried out at the Regional Laboratory of Construction of the Concrete Structures Division of the Civil and Environmental Engineering Faculty at Gdansk University of Technology, the reinforced concrete beams were subjected to destruction...
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Numerical Determination of the Load-Bearing Capacity of a Perforated Thin-Walled Beam in a Structural System with a Steel Grating
PublikacjaThis article presents the results of numerical simulations of a structural system consisting of steel perforated thin-walled beams and a steel grating. The simulations were conducted using the finite element method. The analysis took into account physical and geometric nonlinearity as well as the contact between the steel grating and the beams. The main goal of the research was to develop load-bearing curves for the main beam in...
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Experimental investigations on concrete beams reinforced with CFRP lamellas
PublikacjaPaper presents experimental investigation made on two concrete beams reinforced with internal Carbon Fibre Reinforced Polymer (CFRP) lamellas (i.e. strips, bands). The reinforcement geometrical arrangement was similar as in normal concrete beams reinforced with steel bars and stirrups. The beams were destroyed by the shear forces, as intended. Obtained load-carrying capacities were lower as expected: below 40% of a calculated value....
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Load-carrying capacity and state of effort of tubes made of glass and basalt fibre reinforced polymer filled with concrete
PublikacjaOpisano badania eksperymentalne słupów wykonanych z rur polimerowych zbrojonych włóknami szklanymi i bazaltowymi. Część rur wypełniano wewnątrz betonem. Słupy z wypełnieniem niszczyły się w sposób powolny, wykazując wysoką nośność pokrytyczną, podczas gdy słupy z rur pustych niszczyły się w sposób gwałtowny, niesygnalizowany. Nośności uzyskane eksperymentalnie porównano do nośności obliczonych teoretycznie na podstawie procedur...
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Sylwester Kaczmarek dr hab. inż.
OsobySylwester Kaczmarek ukończył studia w 1972 roku jako mgr inż. Elektroniki, a doktorat i habilitację uzyskał z technik komutacyjnych i inżynierii ruchu telekomunikacyjnego w 1981 i 1994 roku na Politechnice Gdańskiej. Jego zainteresowania badawcze ukierunkowane są na: sieci IP QoS, sieci GMPLS, sieci SDN, komutację, ruting QoS, inżynierię ruchu telekomunikacyjnego, usługi multimedialne i jakość usług. Aktualnie jego badania skupiają...
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Mesoscopic simulations of a fracture process in reinforced concrete beam in bending using a 2D coupled DEM/micro-CT approach
PublikacjaW tej pracy zbadano numerycznie w warunkach 2D złożony proces pękania w krótkiej prostokątnej belce betonowej wzmocnionej jednym prętem podłużnym (bez zbrojenia pionowego) i poddanej quasi-statycznemu zginaniu w trzech punktach. Krytyczne pęknięcie poprzeczne w belce spowodowało jej uszkodzenie podczas doświadczenia. Symulacje numeryczne przeprowadzono klasyczną metodą elementów dyskretnych (DEM). Przyjęto trójfazowy opis betonu:...
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THE METHOD OF ANALYSIS OF DAMAGE REINFORCED CONCRETE BEAMS USING TERRESTRIAL LASER SCANNING
PublikacjaThe authors present an analysis of the possibility to assess deformations and mode of failure of R-C beams using terrestrial laser scanning. As part of experiments carried out at the Regional Laboratory of Construction (at Gdansk University of Technology), reinforced concrete beams were subjected to destruction by bending and by shear. The process of press impact on the reinforced concrete beam was recorded using terrestrial laser...
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Experimental investigations of damage evolution in concrete during bending by continuous micro-CT scanning
PublikacjaThe paper describes experimental investigation results of fracture in notched concrete beams under quasi-static three-point bending. To visualize 3D fracture in concrete under bending, an extended X-ray micro-computed tomography system was used, i.e. the tomography system SkyScan 1173 was connected to the loading machine ISTRON 5569. This combined system enabled to shot images of deforming concrete beams during a continuous deformation...
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Evaluation of pounding effects between reinforced concrete frames subjected to far-field earthquakes in terms of damage index
PublikacjaIn this paper, three different damage indexes were used to detect nonlinear damages in two adjacent Reinforced Concrete (RC) structures considering pounding effects. 2-, 4- and 8-story benchmark RC Moment Resisting Frames (MRFs) were selected for this purpose with 60%, 75%, and 100% of minimum separation distance and also without any in-between separation gap. These structures were analyzed using the incremental dynamic analysis...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublikacjaMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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COMPUTER-AIDED CONSTRUCTION AT DESIGNING REINFORCED CONCRETE COLUMNS AS PER EC
PublikacjaThe article presents the author’s computer program for designing and dimensioning columns in reinforced concrete structures taking into account phenomena affecting their behaviour and information referring to design as per EC. The computer program was developed with the use of C++ programming language. The program guides the user through particular dimensioning stages: from introducing basic data such as dimensions, concrete...
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Modelling reinforced concrete beams under mixed shear-tension failure with different continuous FE approaches
PublikacjaThe paper presents quasi-static numerical simulations of the behaviour of short reinforced concrete beams without shear reinforcement under mixed shear-tension failure using the FEM and four various constitutive continuum models for concrete. First, an isotropic elasto-plastic model with a Drucker-Prager criterion defined in compression and with a Rankine criterion defined in tension was used. Next, an anisotropic smeared crack...
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Response of a fiber-optic Fabry-Pérot interferometer to refractive index and absorption changes – modelling and experiments
PublikacjaThis paper describes how the refractive index and the absorption of investigated substances change the spectrum of the optical radiation at the output of the fiber-optic Fabry-Pérot interferometer. The modeling of the operation of the interferometer takes into account not only the spectra of the refractive index and the absorption of the medium that is inside the cavity, but also spectra of the refractive indices of the core and...
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Analysis of sloping brace stiffness influence on stability and load bearing capacity of a truss
PublikacjaThe paper is focused on the numerical study of stability and load bearing capacity of a truss with side elastic braces. The structure is made in reality. The rotational and sliding brace stiffnesses were taken into account. Linear buckling analysis and non-linear static analysis with geometric and material nonlinearity were performed for the beam and shell model of the truss with respect to the angle of sloping braces. As a result...
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REINFORCED CONCRETE SUPPORTING CONSTRUCTION OF THE STADIUM COVER FOR EURO 2012 IN GDAŃSK
PublikacjaIn the article structural issues that connected with the reinforced concrete supporting construction of the stadium roofing for EURO 2012 in Gdańsk were described. In the first part of the article the concept of stadium foundation were described. In the second the static - strength analysis for two variants fastening together individual foundation elements were made. The two assumed geometrically different concept of foundation...
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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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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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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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Explainable machine learning for diffraction patterns
PublikacjaSerial 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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Evaluation of Asphalt Mixture Low-Temperature Performance in Bending Beam Creep Test
PublikacjaLow-temperature cracking is one of the most common road pavement distress types in Poland. While bitumen performance can be evaluated in detail using bending beam rheometer (BBR) or dynamic shear rheometer (DSR) tests, none of the normalized test methods gives a comprehensive representation of low-temperature performance of the asphalt mixtures. This article presents the Bending Beam Creep test performed at temperatures from −20...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep 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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Artificial Neural Networks in Microwave Components and Circuits Modeling
PublikacjaArtykuł dotyczy wykorzystania sztucznych sieci neuronowych (SNN) w projektowaniu i optymalizacji układów mikrofalowych.Zaprezentowano podstawowe zasady i założenia modelowania z użyciem SNN. Możliwości opisywanej metody opisano wykorzystując przykładowyprojekt anteny łatowej. Przedstawiono różne strategie modelowania układów, które wykorzystują możliwości opisywanej metody w połączeniu zwiedzą mikrofalową. Porównano również dokładność...
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SIMPLIFIED DYNAMIC MODEL OF ROTATING BEAM
PublikacjaIn the paper a hybrid model of rotating beam is presented. It was obtained by using two methods: modal decomposition and spatial discretization. Reduced modal model was built for the system without the load related to inertia forces that occur during beam rotation. This inertia load was next modeled by using the method of simply spatial discretization and combined with reduced modal model. This approach allows to obtain accurate...
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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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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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A survey of neural networks usage for intrusion detection systems
PublikacjaIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn 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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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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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...