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Search results for: artificial neural network, modelling,ship speed, engine fuel consumption
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MODELLING OF TOXIC COMPOUNDS EMISSION IN MARINE DIESEL ENGINE DURING TRANSIENT STATES AT VARIABLE PRESSURE OF FUEL INJECTION
PublicationTransient 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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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublicationThis 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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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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Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
PublicationIn an electric vehicle (EV), using more than one energy source often provides a safe ride without concerns about range. EVs are powered by photovoltaic (PV), battery, and ultracapacitor (UC) systems. The overall results of this arrangement are an increase in travel distance; a reduction in battery size; improved reaction, especially under overload; and an extension of battery life. Improved results allow the energy to be used efficiently,...
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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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NIRCa: An artificial neural network-based insulin resistance calculator
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Artificial neural network based sensorless control ofinduction motor.
PublicationW artykule przedstawiono bezczujnikowy układ sterowania silnikiem indukcyjnym wykorzystujący sztuczne sieci neuronowe (ANN). Sieć neuronową wykorzystano w regulatorze prędkości silnika. Zaprezentowano wyniki badań symulacyjnych.
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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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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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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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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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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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An Instantaneous Engine Speed Estimation Method Using Multiple Matching Synchrosqueezing Transform
PublicationInstantaneous rotational speed measurement of the engine is crucial in routine inspection and maintenance of an automobile engine. Since the contact measurement of rotational speed is not always available, the vibration measurement has been used for noncontact rotational speed estimation methods. Unfortunately, the accuracy of the noncontact estimation methods by analyzing engine vibration frequency is not satisfactory due to the...
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Analysis of Vibration and Acoustic Signals for Noncontact Measurement of Engine Rotation Speed
PublicationThe non-contact measurement of engine speed can be realized by analyzing engine vibration frequency. However, the vibration signal is distorted by harmonics and noise in the measurement. This paper presents a novel method for the measurement of engine rotation speed by using the cross-correlation of vibration and acoustic signals. This method can enhance the same frequency components in engine vibration and acoustic signal. After...
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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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Controlling computer by lip gestures employing neural network
PublicationResults of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....
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A new model of fuel spray shape at early stage of injection in a marine Diesel engine
PublicationIn the cylinders of a marine diesel engine, self-ignition occurs in very shortly time after the fuel injection into the combustion chamber. Therefore, the paper present was to develop a model of diesel fuel spray for the early stage of fuel spray for in marine diesel engine. There were taken into consideration the main aspects technical such as nozzle diameter of marine engine injector and backpressure in combustion chamber. In...
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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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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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On thermal and Flow Expert Systems Based on Artificial Neural Network (ANN)
PublicationZaprezentowano możliwość realizacji jednego z zadań systemów eksperckich, polegającego na określaniu rozmiaru eksploatacyjnej degradacji parametrów geometrycznych układów łopatkowych turbin. Dyskusję przeprowadzono w oparciu o zastosowanie wybranego typu sztucznej sieci neuronowej (SSN). Badano jakość i dokładność polegającą na dobrej identyfikacji rozmiaru degradacji przez tę wybraną SSN wykrywającą rozmiar degradacji geometrycznej....
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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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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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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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Flexible syngas-biogas-hydrogen fueling spark-ignition engine behaviors with optimized fuel compositions and control parameters
PublicationThis paper presents the results research on the optimal fuel compositions and the control parameters of the spark ignition engine fueled with syngas-biogas-hydrogen for the purpose of setting up a flexible electronic control unit for the engine working in a solar-biomass hybrid renewable energy system. In syngas-biogas-hydrogen mixture, the optimal content of hydrogen and biogas is 20% and 30%, respectively. Exceeding these thresholds,...
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublicationHoning 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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Influence of the engine cooling down period during short car stops on the average fuel consumption
PublicationW publikacji przedstawiono wpływ schłodzenia silnika podczas krótkich postojów pomiędzy jazdami na średnie zużycie paliwa. Przeprowadzono własne pomiary w czasie jazd miejskich w Gdańsku. Użyto samochodu osobowego z silnikiem o objętości skokowej 2 dm^3 z zapłonem siskrowym. Mierzono zużycie paliwa na trasach o długości 3-10 km. Krótko opisano sposoby wstępnego podgrzania silnika przed rozruchem.
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Limitation of Floating-Point Precision for Resource Constrained Neural Network Training
PublicationInsufficient availability of computational power and runtime memory is a major concern when it comes to experiments in the field of artificial intelligence. One of the promising solutions for this problem is an optimization of internal neural network’s calculations and its parameters’ representation. This work focuses on the mentioned issue by the application of neural network training with limited precision. Based on this research,...
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Neural network modelling of the influence of channelopathies on reflex visual attention
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The Effect of Oxygenated Diesel-N-Butanol Fuel Blends on Combustion, Performance, and Exhaust Emissions of a Turbocharged CRDI Diesel Engine
PublicationThe article deals with the effects made by using various n-butanol-diesel fuel blends on the combustion history, engine performance and exhaust emissions of a turbocharged four-stroke, four-cylinder, CRDI 1154HP (85 kW) diesel engine. At first, load characteristics were taken when running an engine with normal diesel fuel (DF) to have ‘baseline’ parameters at the two ranges of speed of 1800 and 2500 rpm. Four a fossil diesel (class...
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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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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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Quantitative Assessment of Operation of Ship Main Diesel Engine
PublicationOperation of ship propulsion system is associated with realization of definite operational goals. If to elements of the system the operational reliability strategy could be applied, the situation would be very simple as existing conditions would unambiguously determine application of means being on hand. However decision to reject application of the strategy (even if hypothetical) becomes obvious with a view of necessity of ensuring...
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Advances in Modelling and Analysis of Strength of Corroded Ship Structures
PublicationThe present study reviews the recent advances in modelling and analyses the strength of corroded ship structures. Firstly, the time-variant methodologies that consider only the mean structural element thickness loss due to corrosion degradation are identified. Corrosion degradation is regarded as the phenomenon that causes uneven thinning of specimens. This has been captured by various researchers as the loss of mechanical properties...
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublicationThe 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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On possible lowering fuel oil consumption by differentiating loads on ship diesel engines running in parrallel.
PublicationPodano możliwości zmniejszenia zużycia paliwa przez silniki okrętowe pracujące równolegle dzieki różnicowaniu ich obciążeń eksploatacyjnych. Zaprezentowano podstawy teoretyczne oraz sposób postępowania przy pomiarach zużycia paliwa w czasie rzeczywistym.
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Neural network agents trained by declarative programming tutors
PublicationThis paper presents an experimental study on the development of a neural network-based agent, trained using data generated using declarative programming. The focus of the study is the application of various agents to solve the classic logic task – The Wumpus World. The paper evaluates the effectiveness of neural-based agents across different map configurations, offering a comparative analysis to underline the strengths and limitations...
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The influence of the fuel spray nozzle geometry on the exhaust gas composition from the marine 4-stroke diesel engine
PublicationThe paper presents experimental research on a 4-stroke, 3-cylinder, turbocharged AL25/30 Diesel engine. Research consisted in investigating the effect of the geometry of the fuel injectors on the exhaust gas composition from the engine. During measurements, the engine was operated with a regulator characteristic of a load range from 40 kW to 280 kW, made by electric water resistance. The engine was mechanically coupled to the electric...
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The system combined of low-speed marine diesel engine and steam turbine in ship propulsion applications
PublicationPrzedstawiono koncepcje okrętowego układu kombinowanego silnik wolnoobrotowy tłokowy- turbina parowa, wykorzystującego ciepło zawarte w spalinach wylotowych.Porównano układ kombinowany dużej mocy dla dwóch silników tłokowych porównywalnych mocy z punktu widzenia termodynamicznego.
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Taking decisions in the diagnostic intelligent systems on the basis information from an artificial neural network
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Artificial Neural Network (ANN)-Based Voltage Stability Prediction of Test Microgrid Grid
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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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Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data
PublicationTo analyse the behaviour of marine diesel engines in unsteady states for different purposes, for example to determine the fuel consumption or emissions level, to adjust the control strategy, to manage the maintenance, etc., a goal-based mathematical model that can be easily implemented for simulation is necessary. Such a model usually requires a wide range of operating data, measured on a test stand. This is a time-consuming process...
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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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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New Concept of Numerical Ship Motion Modelling for Total Ship Operability Analysis by Integrating Ship and Environment Under One Overall System
PublicationThe paper presents a new concept of overall ship motion modelling for application to total ship operability. The delivered model is a multi-phase and includes both submerged part of ship’s hull and the surrounding water as a unique body. The Discrete Finite Element Method is applied. The model is successfully examined and illustrated for a selected AHTS.
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Analysis of the structure of the atomized fuel spray with marine diesel engine injector in the early stage of injection
PublicationThis paper presents the results of the experimental research of the atomized fuel spray with the marine diesel engine injector in the constant volume chamber. The specificity of the phenomena occurring in the marine engine cylinder was the reason to use the optical visualisation method in the studies – the Mie scattering technique. This work presents an analysis of the influence of different geometry of outlet orifice and opening...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublicationPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Intelligent turbogenerator controller based on artifical neural network
PublicationThe paper presents a desing of an intelligent controller based on neural network (ICNN). The ICNN ensures at the same time two fundamental functions : the maintaining of generator voltage at the desired value and the damping of the electromechanical oscillations. Its performance is evaluted on a single machine infinite bus power system through computer simulations. The dynamic and transient operation of the proposed controller...