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Search results for: combined method, sea conditions, ship speed, fuel consumption, powertrain load, artificial neural network (ann)
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A unified approach to the analysis of electric energy and fuel consumption of cars in city traffic
PublicationForecasting fuel and electricity consumption is an important factor determining the direction of changes in road engineering solutions, traffic management, selection of routes for public transport and development more efficient car drive systems. With a reliable and easy-to-use computational tool, it is possible to reduce the consumption of primary energy sources and reduce the emission of toxic compounds in cities. An analysis...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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STUDY ON THE RELATIONSHIP BETWEEN VEHICLE MAINTENANCE AND FUEL CONSUMPTION
PublicationA contemporary road vehicle (RV) is a rather complex system, consisting of a large number of subsystems, assemblies, units, and elements (parts). While operating, an RV interacts with the environment, and its elements interact with each other. Consequently, the properties (parameters) of these elements change in the process - hardness, roughness, size, relative position, gapping, etc. A partial solution to the presented problems...
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Modelling of a medium-term dynamics in a shallow tidal sea, based on combined physical and neural network methods
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Comparison of single best artificial neural network and neural network ensemble in modeling of palladium microextraction
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Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics
PublicationPrzedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.
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Optimization Model to Manage Ship Fuel Consumption and Navigation Time
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublicationThis work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...
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Comparative study of methods for artificial neural network training.
PublicationPrzedstawiono wyniki badań porównawczych następujących metod uczenia sieci neuronowych: propagacji wstecznej błędów, rekursywnej metody najmniejszych kwadratów, metody Zangwill'a i algorytmów ewolucyjnych. Badania dotyczyły projektowania adaptacyjnego regulatora neuronowego napięcia generatora synchronicznego.
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublicationTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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Experimental study on the selected aspects of bow thruster generated flow field at ship zero-speed conditions
PublicationThe paper presents the results of experimental study on the interaction between the bow thrusters understood as the flow field changes generated by bow tunnel thruster in deep water conditions operated as a single and twin units. The research was limited to zero-speed case for the ship dead in the water. The influence of the hull form and jet spread between the neighbouring thrusters for several combinations of the applied bow...
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The influence of the geographic positioning system error on the quality of ship magnetic signature reproduction based on measurements in sea conditions
PublicationIn previous studies, the authors performed the magnetic signature reconstruction of the marine ship Zodiak as part of the measurement campaign focused on recording magnetic data and the relative position of a ship during its passage over a magnetometer immersed on the testing ground. A high degree of representation of the magnetic signature was obtained. However, the recorded measurement data revealed new patterns of the multidipole model...
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A method for determination of fuel oil consumption saving by stepvise differetiating loads on ship diesel engines running in paralel.
Publicationprzedstawiono metodykę wyznaczania oszczędniości w zużyciu paliwa dla silników pracujących na wspólną sieć w wyniku różnicowania ich obciążeń oraz stosowania metody krokowych zmian obciążenia. znajomość charakterystyk zużycia paliwa poszczególnych silników oraz histogramu rozkładu obciążeńeksploatacyjnych pozwala po zastosowaniu proponowanej metody na wyznaczanie oszczędności w zuzyciu paliwa.
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Neural network training with limited precision and asymmetric exponent
PublicationAlong 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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Determination of probabilities defining safety of a sea-going ship during performance of a transportation task in stormy weather conditions
PublicationThe paper presents the possibility of applying the theory of semi-Markov processes to determine the limiting distribution for the process of changes of technical states being reliability states of the systems of sea-going ships significantly affecting safety of such ships, which include main engine, propeller and steering gear. The distribution concerns the probabilities of occurrence of the said states defined for a long time...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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UNDERWATER NOISE GENERATED BY A SMALL SHIP IN THE SHALLOW SEA
PublicationStudy of the sea noise has been a subject of interest for years. The first work of this scope were published at the turn of the twentieth century by Knudsen (KNUDSEN et al., 1948) and G. Wenz (WENZ, 1962). Disturbances called "shipping noise" are one of the important components of the sea noise. In this work the results of an experimental research of underwater noise produced by a small ship of a classic propulsion are...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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NIRCa: An artificial neural network-based insulin resistance calculator
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Tyre rolling resistance and its influence on fuel consumption
PublicationRolling resistance of tyres is one of the major resistive forces acting on any wheeled vehicle. Unfortunately, it is also one of the forces very difficult to measure. It is estimated that in certain traffic conditions (like for example constant speed driving with slow or moderate speed) so called Rolling Resistance Impact Factor may be as high as 0.3. This means that reduction of rolling resistance by 50% would lead to 15% of energy...
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Automatic singing quality recognition employing artificial neural networks
PublicationCelem 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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Dynamic response of the PEM fuel cell to variable load conditions
PublicationOpisano układ zasilania oparty na 2 ogniwach paliwowych typu PEM o mocy 1.2 kW każde. Omówiono problem ograniczenie ogniwa paliwowego przez drugą zasadę termodynamiki. Przedstawiono charakterystyki układu w zależności od sygnału obciążenia typu: skok jednostkowy, półsinusoidalny, trójkątny, prostokątny i trapezowy.
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublicationBeta-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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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe 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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Determining and visualizing safe motion parameters of a ship navigating in severe weather conditions
PublicationThe paper presents a method of determining, organizing and displaying ship collision avoidance information, which is based on the Collision Threat Parameters Area (CTPA) technique. The method makes it possible to visualize navigational threats as well as possible collision avoidance manoeuvres. The solution is focused on supporting navigation in severe weather conditions. Normally collision avoidance decisions are made taking into...
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Propagation of Ship-Generated Noise in Shallow Sea
PublicationContamination of sea environment by noise and any energy radiated to water constitutes today a problem to which more and more attention is paid, in view, a.o., of consequences of an impact of these factors onto marine fauna. European Union has introduced a directive by which EU countries are made responsible to undertake efforts aimed at reaching a good envirenmental status of European seas by 2020. A main source of underwater...
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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Artificial Neural Network based fatigue life assessment of riveted joints in AA2024 aluminum alloy plates and optimization of riveted joints parameters
PublicationThe objective of this paper is to provide the fatigue life of riveted joints in AA2024 aluminum alloy plates and optimization of riveted joints parameters. At first, the fatigue life of the riveted joints in AA2024 aluminum alloy plates is obtained by experimental tests. Then, an artificial neural network is applied to estimate the fatigue life of riveted lap joints based on the number of lateral and longitudinal holes, punch pressure,...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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An application of simulation model of fuel consumption in diagnostic system of wheeled tractors
PublicationAn application of computer controlled fuel injection systems in vehicle engines and growing demands concerning toxic substances emission and fuel consumption was a main reason for OBD (On Board Diagnosis) development. In spite of a great technological development, only some tractors are equipped in diagnostic systems. On board diagnostic is strongly connected with emission demands and does not concern other important vehicle functions. In...
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Artificial-Neural-Network-Based Sensorless Nonlinear Control of Induction Motors
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Ultracapacitor modeling and control with discrete fractional order artificial neural network
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Artificial Neural Network-Based Sensorless Nonlinear Control Of Induction Motors
PublicationW niniejszym artykule przedstawiono strukturę sztucznej sieci neuronowej służącej do korygowania działania układu estymacji prędkości kątowej wirnika. Odtworzona prędkość kątowa wirnika zostały wykorzystane w bezczujnikowym układzie sterowania silnikiem indukcyjnym pracującym w zamkniętej pętli sprzężenia prędkościowego.Przedstawiono wyniki badań eksperymentalnych z silnikiem o mocy 1,1kW.
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Research of Influence Electric Conditions Combined ElectroDiamond Processing by on Specific Consumption of Wheel*
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublicationPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
PublicationArtificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper pesents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to...
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Application of ANN and PCA to two-phase flow evaluation using radioisotopes
PublicationIn the two-phase flow measurements a method involving the absorption of gamma radiation can be applied among others. Analysis of the signals from the scintillation probes can be used to determine the number of flow parameters and to recognize flow structure. Three types of flow regimes as plug, bubble, and transitional plug – bubble flows were considered in this work. The article shows how features of the signals in the time and...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublicationDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublicationA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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Some aspects of noise generated by a small ship in the shallow sea
PublicationThe passing and underwater moving objects produce the noises of variable intensity, which significantly increase the overall level of noise in the sea. This applies to both the sonic and ultrasonic range. The excessive levels of underwater noise adversely affects the so-called underwater acoustic climate and is the reason why this phenomenon is intensively investigated from the number of years. The results of experimental work...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Computational simulation of motion of a rescue module during its launching from ship at rough sea
PublicationThis paper is a continuation of the work titled : “A comp utational model for simulation of motion of rescue module during its launching from stern ramp of a ship at rough sea”. It presents results of computer simulations of motion of a rescue module with embarked persons during its launching on rollers along stern ramp of a ship at rough sea. The simulations were conducted for a selected ship fitted with a launching ramp , for...
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Quantitative risk assessment of new ship designs in damage conditions
PublicationThe paper is devoted to safety of ships in damage conditions. The novel contribution of the paper is connected with a new Multi-Task ship (MT-ship) design at the preliminary stage of design. There are a few problems at the preliminary stage that should be considered. One problem is connected with if the quantitative risk-based method is a reliable and formal method for safety assessment of such the new design (MT-ship) in damage...
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The Influence of External Load on the Performance of Microbial Fuel Cells
PublicationIn this work, the effect of the external load on the current and power generation, as well as on the pollutant removal by microbial fuel cells (MFCs), has been studied by step-wise modifying the external load. The load changes included a direct scan, in which the external resistance was increased from 120 Ω to 3300 Ω, and a subsequent reverse scan, in which the external resistance was decreased back to 120 Ω. The reduction in the...
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A method of determining and visualizing safe motion parameters of a ship navigating in restricted waters
PublicationThe paper presents a method of displaying ship collision avoidance information which is based on an unconventional Collision Threat Parameters Area (CTPA) technique. The solution presented here extends CTPA's functionality from past works by supporting navigation in restricted waters and handling ship domains analytically instead of numerically. It visualizes potential navigational threats as well as possible collision avoidance...