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Wyniki wyszukiwania dla: artificial neural network, modelling,ship speed, engine fuel consumption
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublikacjaThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublikacjaIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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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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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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The Development of a Combined Method to Quickly Assess Ship Speed and Fuel Consumption at Different Powertrain Load and Sea Conditions
PublikacjaDecision support systems (DSS) recently have been increasingly in use during ships operation. They require realistic input data regarding different aspects of navigation. To address the optimal weather routing of a ship, which is one of the most promising field of DSS application, it is necessary to accurately predict an actually attainable speed of a ship and corresponding fuel consumption at given loading conditions and predicted...
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The Analysis of Overall Ship Fuel Consumption in Acceleration Manoeuvre using Hull-Propeller-Engine Interaction Principles and Governor Features
PublikacjaThe problem of reduction of greenhouse gas emissions in shipping is currently addressed by many research works and related industries. There are many existing and visionary technologies and ideas, which are conceptually defined or practically realised. This goal can be achieved in different ways, and reducing fuel consumption is one of the major methods. In these circumstances, the aim of this study is to analyse the possibility...
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Artificial neural network controller for underwater ship hull operation robot.
PublikacjaZaproponowano model matematyczny pojazdu podwodnego, który w uproszczonej wersji spełnia warunki dynamiki odpowiadające głowicy roboczej podwodnego robota. Uwzględniono niektóre czynniki oddziałujące na ruch podwodnej głowicy roboczej, jak np. gęstość wody oraz siły odśrodkowe i wypornościowe. Przedstawiono układ sterowania, w którym zastosowano regulator oparty na bazie sieci neuronowych, za pomocą którego można sterować...
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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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Impact of Propeller Emergence on Hull, Propeller, Engine, and Fuel Consumption Performance in Regular Head Waves
PublikacjaIn this study, the impact of propeller emergence on the performance of a ship (speed), propeller (thrust, torque, and RPM), a diesel engine (torque and RPM) and fuel consumption are analysed under severe sea conditions. The goal is to describe the variation in the system variables and fuel consumption rather than analysing the motion of the ship or the phenomenon of propeller ventilation in itself. A mathematical model of the...
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Investigating Fuel Injection Strategies to Enhance Ship Energy Efficiency in Wave Conditions
PublikacjaThe prediction of fuel consumption and resulting transportation costs is a crucial stage in ship design, particularly for conditions involving motion in waves. This study investigates the real-time fuel consumption of a container ship when sailing in waves. The overall ship performance is evaluated using a novel non-linear coupled hull-engine-propeller interaction model. A series of towing tank experiments for hull resistance in...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublikacjaW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wykorzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublikacjaW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wyko-rzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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The effect of numerical 2D and 3D FEM element modelling on strain and stress distributions at laser weld notches in steel sandwich type panels
PublikacjaLike other means of transport, merchant ships face the problem of increasing requirements concerning the environment protection, which, among other issues, implies the reduction of fuel consumption by the ship. Here, the conventional approach which consists in making use of higher strength steels to decrease the mass of the ship hull can be complemented by the use of new steel structures of sandwich panel type. However, the lack...
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TEST METHOD FOR DETERMINING THE CHEMICAL EMISSIONS OF A MARINE DIESEL ENGINE EXHAUST IN OPERATION
PublikacjaThe article briefly describes the problem of air pollution caused by sea-going ships and the resulting restrictions on the emission of toxic and harmful chemical compounds in the exhaust of marine engines, introduced by the International Maritime Organization (IMO) under the International Convention for the Prevention of Sea Pollution from Ships (MARPOL 73/78). Such emissions provide a significant metrological problem, not only...
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EXPERIMENTAL RESEARCH ON INFLUENCE OF THE FUEL NOZZLE GEOMETRY ON THE FUEL CONSUMPTION OF THE MARINE 4-STROKE DIESEL ENGINE
PublikacjaThe article presents experimental research that has been carried out on a marine, 4-stroke, 3-cylinder, turbocharged engine. During testing, the engine operated at a constant rotational speed of 750 rpm and a load from 0 kW to 280 kW. The engine was fuelled by diesel oil of known specification and loaded by electric generator with water resistance. The fuel consumption was measured during the engine operation with fuel nozzles...
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Ship Resistance Prediction with Artificial Neural Networks
PublikacjaThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Synteza układu sterowania statkiem morskim dynamicznie pozycjonowanym w warunkach niepewności
PublikacjaNiniejsza monografia obejmuje zagadnienia związane z syntezą układu dynamicznego pozycjonowania statku w środowisku morskim z zastosowaniem wybranych nieliniowych metod sterowania. W ramach pracy autorka rozważała struktury sterowania z zastosowaniem wektorowej adaptacyjnej metody backstep oraz metod jej pokrewnych, takich jak regulatory MSS (ang. multiple surface sliding), DSC (ang. dynamic surface control), NB (ang. neural backstepping)....
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Badanie stanu nawierzchni drogowej z wykorzystaniem uczenia maszynowego
PublikacjaW artykule opisano budowę systemu informowania o stanie nawierzchni drogowej z wykorzystaniem metod cyfrowego przetwarzania obrazów oraz uczenia maszynowego. Efektem wykonanych prac badawczych jest eksperymentalna platforma, pozwalająca na rejestrację uszkodzeń na drogach, system do analizy, przetwarzania i klasyfikacji danych oraz webowa aplikacja użytkownika do przeglądu stanu nawierzchni w wybranej lokalizacji.
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Electromagnetic Modeling of Microstrip Elements Aided with Artificial Neural Network
PublikacjaThe electromagnetic modeling principle aided withartificial neural network to designing the microwave widebandelements/networks prepared in microstrip technology is proposedin the paper. It is assumed that the complete information is knownfor the prototype design which is prepared on certain substratewith certain thickness and electric permittivity. The longitudinaland transversal dimensions of new design...
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Analysis of different tillage implements with respect to reduced fuel consumption, tractor operating speed and its wheel slippage
PublikacjaNowadays the prices of agricultural farm produced products are increasing with ant-speed and the prices of input for raising crops are increasing with rocket-speed. Therefore, there is a dire need to conduct some important studies to innovate the techniques which can lower the costs of crop production. In this context, this study was conducted to evaluate the consumption of fuel at different tillage implements, tractor operating...
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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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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublikacjaA 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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Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services
PublikacjaThis paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublikacjaThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublikacjaExpert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublikacjaArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Design of Microstrip UWB Balun Using Quasi-TEM Approach Aided by the Artificial Neural Network
PublikacjaThe design procedure for UWB balun realized in the microstrip technology is proposed in the paper. The procedure applies Artificial Neural Network which corrects the dimensions of the approximate design found by appropriate scaling of the dimensions of the prototype. The scale coefficients for longitudinal and transverse dimensions of microstrip lines are determined from electromagnetic modeling based on transmission line equations....
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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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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis 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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The possibilities of using of the engine multidimensional charakteristics in fuel consumption prediction
PublikacjaDokument przedstawia możliwości prognozowania zużycia paliwa z wykorzystaniem wielowymiarowej charakterystyki zużycia silnika. Zdefiniowane zostały charakterystyki wielowymiarowe silnika.
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Artificial Neural Network for Multiprocessor Tasks Scheduling
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Approximation task decomposition for artificial neural network.
PublikacjaW pracy przedstawiono wpływ dekompozycji zadania na czasochłonność projektowania oraz dokładność i szybkość obliczeń sztucznej sieci neuronowej wykorzystanej do rozwiązania rzeczywistego problemu technicznego, którego matematyczny model był znany. Celem obliczeń prowadzonych przez sieć neuronową było określenie wartości współczynnika przepływu m na podstawie znajomości wartości: przewodności dźwiękowej C i średnicy przewodu d (a...
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Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
PublikacjaThe present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases...
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Analysis of the macrostructure of the fuel spray atomized with marine engine injector
PublikacjaOne of the main problem influencing the combustion process in the cylinder of the marine engine is an fuel spray phenomena. The parameters describing the shape of the fuel spray are named macro parameters. This article presents the research results of the macrostructure parameters of the fuel spray atomized with the marine engine injector. The research were carried out by optical visualization measurement method of Mie scattering....
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Comparison of single best artificial neural network and neural network ensemble in modeling of palladium microextraction
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Biotrickling filtration of n-butanol vapors: process monitoring using electronic nose and artificial neural network
PublikacjaBiotrickling filtration is one of the techniques used to reduce odorants in the air. It is based on the aerobic degradation of pollutants by microorganisms located in the filter bed. The research presents the possibility of using the electronic nose prototype combined with artificial neural network for biofiltration process monitoring in terms of reduction in n-butanol concentration and odour intensity of treated air. The study...
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Optimization Model to Manage Ship Fuel Consumption and Navigation Time
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The influence of fuel type on heat balance of medium-speed engine
PublikacjaW artykule zaprezentowano analizę wpływu rodzaju zastosowanego paliwa na bilans cieplny silników średnioobrotowych stosowanych w energetyce stacjonarnej. Przedmiotem analizy są silniki ZS i ZI zasilane gazem ziemnym oraz silniki ZS zasilane olejem napędowym. Dodatkowo analizę uzupełniono o wyniki obliczeń wykonanych dla silników dwupaliwowych, tzn. silników, w których zapłon mieszanki paliwowo gazowej realizowany jest przez pilotażowy...
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Fuel systems of high power stationary engine
PublikacjaThe use of alternative fuels and, in the future, synthetic fuels has forced changes in the design of fuel supply systems in internal combustion engines. When operating a stationary engine at constant load, the possibility of using lean fuel mixtures appears. The selection of a precise operating mixture ignition system requires changes in traditional fuel systems. The article presents the current designs of fuel supply systems and...
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A unified approach to the analysis of electric energy and fuel consumption of cars in city traffic
PublikacjaForecasting 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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An application of simulation model of fuel consumption in diagnostic system of wheeled tractors
PublikacjaAn 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 fatigue life assessment of friction stir welding AA2024-T351 aluminum alloy and multi-objective optimization of welding parameters
PublikacjaIn this paper, the fracture behavior and fatigue crack growth rate of the 2024-T351 aluminum alloy has been investigated. At first, the 2024-T351 aluminum alloys have been welded using friction stir welding procedure and the fracture toughness and fatigue crack growth rate of the CT specimens have been studied experimentally based on ASTM standards. After that, in order to predict fatigue crack growth rate and fracture toughness,...
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Comparative study of methods for artificial neural network training.
PublikacjaPrzedstawiono 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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STUDY ON THE RELATIONSHIP BETWEEN VEHICLE MAINTENANCE AND FUEL CONSUMPTION
PublikacjaA 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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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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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublikacjaThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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MODELLING OF TOXIC COMPOUNDS EMISSION IN MARINE DIESEL ENGINE DURING TRANSIENT STATES AT VARIABLE PRESSURE OF FUEL INJECTION
PublikacjaTransient states are an important part of the spectrum of engine loads, especially the traction engines. In the case of marine diesel engines, transient states are of particular importance in reducing the analysis of motion units for special areas and maneuvering in port, the participation of transient states in the load spectrum significantly increases, also, the emission of toxic compounds from this period increases proportionally....
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting 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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Resource constrained neural network training
PublikacjaModern 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...