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Wyniki wyszukiwania dla: sztuczna inteligencja
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Optimisation of turbine shaft heating process under steam turbine run-up conditions
PublikacjaAn important operational task for thermal turbines during run-up and run-down is to keep the stresses in the structural elements at a right level. This applies not only to their instantaneous values, but also to the impact of them on the engine lifetime. The turbine shaft is a particularly important element. The distribution of stresses depends on geometric characteristics of the shaft and its specific locations. This means a groove manufactured...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant
PublikacjaIn the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR) working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller...
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Inteligencja zespołowa
PublikacjaPrzedstawiono przegląd zespołowego przetwarzania informacji, uczenia się i podejmowania decyzji. Omówiono algorytmy ewolucyjne, roju, mrówkowe, immunologiczne, sieci neuronowe, współpracę agentów, modelowanie indywiduowe oraz przykładowe środowisko modelowania zespołowego.
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Metoda i algorytmy sterowania procesami miksowania dźwięku za pomocą gestów w oparciu o analizę obrazu wizyjnego
PublikacjaGłównym celem rozprawy było opracowanie systemu miksowania dźwięku za pomocą gestów rąk wykonywanych w powietrzu oraz zbadanie możliwości oferowanych przez takie rozwiązanie w porównaniu ze współczesną metodą miksowania sygnałów fonicznych, wykorzystującą środowisko komputera. Opracowany system rozpoznaje zarówno dynamiczne jak i statyczne gesty rąk. Rozpoznawanie gestów dynamicznych zrealizowano w oparciu o metody logiki rozmytej...
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Jan Daciuk dr hab. inż.
OsobyJan Daciuk uzyskał tytuł zawodowy magistra na Wydziale Elektroniki Politechniki Gdańskiej w 1986 roku, a doktorat na wydziale Elektroniki, Telekomunikacji i Informatyki PG w 1999. Pracuje na Wydziale od 1988 roku. Jego zainteresowania naukowe obejmują zastosowania automatów skończonych w przetwarzaniu języka naturalnego i przetwarzaniu mowy. Spędził ponad cztery lata w europejskich uniwersytetach i instytutach naukowych, takich...
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Karol Dziedziul dr hab.
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Automated Valuation Model based on fuzzy and rough set theory for real estate market with insufficient source data
PublikacjaObjective monitoring of the real estate value is a requirement to maintain balance, increase security and minimize the risk of a crisis in the financial and economic sector of every country. The valuation of real estate is usually considered from two points of view, i.e. individual valuation and mass appraisal. It is commonly believed that Automated Valuation Models (AVM) should be devoted to mass appraisal, which requires a large...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublikacjaTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Evaluation of a company’s image on social media using the Net Sentiment Rate
PublikacjaVast amounts of new types of data are constantly being created as a result of dynamic digitization in all areas of our lives. One of the most important and valuable categories for business is data from social networks such as Facebook. Feedback resulting from the sharing of thoughts and emotions, expressed in comments on various products and services, is becoming the key factor on which modern business is based. This feedback is...
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Outlier detection method by using deep neural networks
PublikacjaDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Akustyczna analiza parametrów ruchu drogowego z wykorzystaniem informacji o hałasie oraz uczenia maszynowego
PublikacjaCelem rozprawy było opracowanie akustycznej metody analizy parametrów ruchu drogowego. Zasada działania akustycznej analizy ruchu drogowego zapewnia pasywną metodę monitorowania natężenia ruchu. W pracy przedstawiono wybrane metody uczenia maszynowego w kontekście analizy dźwięku (ang.Machine Hearing). Przedstawiono metodologię klasyfikacji zdarzeń w ruchu drogowym z wykorzystaniem uczenia maszynowego. Przybliżono podstawowe...
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Ocena wpływu drgań komunikacyjnych na budynki za pomocą maszynowego uczenia
PublikacjaDrgania komunikacyjne mogą powodować spękania tynków, zarysowania a nawet zawalenie się budynku. Pomiary na rzeczywistych obiektach są pracochłonne i kosztowne, a nie zawsze uzasadnione. Celem jest utworzenie modelu, dzięki któremu można przewidzieć zagrożenie szkodliwego oddziaływania drgań komunikacyjnych na budynek. Po przeprowadzeniu własnych badań pomiarowych oraz analizie literatury utworzono model oparty na Maszynach Wektorów...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublikacjaPredicting 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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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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New approach to railway noise modeling employing Genetic Algorithms
PublikacjaMain goal of this paper was to describe an innovative method of noise prediction based on Genetic Algorithms. First part of the paper addresses the problem of growing noise, mainly in the context of a unified method for measuring noise. Further, Genetic Algorithms are described with regards to their fundamental features. Further a description is provided as to how Genetic Algorithms were used in the area of noise modeling. Next...
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Rafał Łangowski dr inż.
OsobyDr inż. Rafał Łangowski jest absolwentem Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej (studia magisterskie ukończył z wyróżnieniem w 2003 roku). W roku 2015 uzyskał stopień doktora nauk technicznych w dyscyplinie automatyka i robotyka. Pracę doktorską pt. "Algorytmy alokacji punktów monitorowania jakości w systemach dystrybucji wody pitnej" obronił z wyróżnieniem na Wydziale Elektrotechniki i Automatyki. W latach...
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"Computing with words" concept applied to musical information retrieval
PublikacjaW artykule zaproponowano wykorzystanie koncepcji "przetwarzania słów języka naturalnego" do znalezienia związku pomiędzy wybranymi parametrami dźwięków muzycznych a subiektywnie postrzeganą barwą. W pierwszej kolejności przedstawiono klasyczne metody mapowania parametrów mierzalnych i ich subiektywnych odpowiedników, następnie zbudowano bazę wiedzy w oparciu o wyniki testów subiektywnych. W procesie obróbki wykorzystano metodę...
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Evaluation of the factors influencing business bankruptcy risk in Poland
PublikacjaThis article is devoted to the issue of assessing the causes of business failure. The presented studies answer two research questions – what are the causes of corporate bankruptcies in Poland and how to more efectively predict the scale of bankruptcies in the country. The author has conducted a study to analyze the specic endogenous and exogenous causes of company bankruptcy depending on the type of the bankruptcy with consideration...
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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublikacjaDapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...
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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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Forecasting of currency exchange rates using artificial neural networks
PublikacjaW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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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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Application of Artificial Neural Networks in Investigations of Steam Turbine Cascades
PublikacjaZaprezentowano wyniki badań numerycznych zastosowania sieci neuronowych przy obliczeniach przepływów w palisadach turbin parowych. Na podstawie uzyskanych wyników wykazano, że sieci neuronowe mogą być używane do szacowania przestrzennego rozkładu parametrów przepływu, takich jak entalpia, entropia, ciśnienie czy prędkość czynnika w kanale przepływowym. Omówiono również zastosowania tego typu metod przy projektowaniu palisad, stopni...
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublikacjaThis 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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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Optymalizacja struktur i obliczeń w sieciach neuronowych - 2023
Kursy Online3 semestr studiów II stopnia, kierunek Informatyka, specjalność Uczenie Maszynowe
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Optymalizacja struktur i obliczeń w sieciach neuronowych
Kursy Online3 semestr studiów II stopnia, kierunek Informatyka, specjalność Uczenie Maszynowe
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Optymalizacja struktur i obliczeń w sieciach neuronowych - 2024
Kursy Online3 semestr studiów II stopnia, kierunek Informatyka, specjalność Uczenie Maszynowe
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublikacjaMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Algorytmy klasyfikacji i uczenia w rozpoznawaniu treści
PublikacjaZadanie klasyfikacji treści może zostać podzielone na dwa etapy: ekstrakcji cech istotnych dla podziału na klasy oraz etapu klasyfikacji na podstawie cech wyznaczonych w poprzednim etapie. Dzięki takiemu podziałowi, możliwe jest użycie w drugim etapie standardowych algorytmów budowy (uczenia) klasyfikatorów, takich klasyfikator bayesowski, drzewa decyzyjne, sztuczne sieci neuronowe czy metoda wektorów wspierających (SVM). Przy...
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Extracting concepts from the software requirements specification using natural language processing
PublikacjaExtracting concepts from the software require¬ments is one of the first step on the way to automating the software development process. This task is difficult due to the ambiguity of the natural language used to express the requirements specification. The methods used so far consist mainly of statistical analysis of words and matching expressions with a specific ontology of the domain in which the planned software will be applicable....
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublikacjaHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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Analysis of odour interactions in model gas mixtures using electronic nose and fuzzy logic
PublikacjaMeasurement and monitoring of air quality in terms of odour nuisance is an important problem. Although the source of these nuisances is different (e.g. wastewater treatment plants, municipal landfills), their common feature is that they are a complex mixture of odorants with different odour thresholds. An additional problem is occurrence of the odour interactions between mixture components. From a practical point of view, it would...
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Chemometric Evaluation of WWTPs’ Wastewaters and Receiving Surface Waters in Bulgaria
PublikacjaWastewater treatment plant (WWTP) installations are designed and operated to reduce the quantity of pollutants emitted to surface waters receiving treated wastewaters. In this work, we used classical instrumental studies (to determine chemicals and parameters under obligations put with Directive 91/271/EEC), ecotoxicological tools (Sinapis alba root growth inhibition (SA-RG) and Heterocypris incongruens mortality (MORT) and growth...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublikacjaIn this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...
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Widzenie Komputerowe 2023/2024 semestr zimowy
Kursy OnlineKurs do przedmiotu Widzenie Komputerowe prowadzonego w semestrze zimowym 2023/2024
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Knowledge representation of motor activity of patients with Parkinson’s disease
PublikacjaAn approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...
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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Czasopisma -
Wykorzystanie sieci neuronowych do diagnostyki poprawności wykonania płytek drukowanych
PublikacjaArtykuł opisuje stanowisko badawcze do diagnostyki optycznej poprawności wykonania płytek drukowanych przesuwających się po taśmie produkcyjnej. Diagnostyka optyczna dokonywana jest poprzez kamerę. Obraz z kamery przekazywany jest do komputera PC, gdzie trafia do zaprojektowanego systemu diagnostycznego, zaimplementowanego w środowisku Matlab. Po odpowiednim przetworzeniu obrazy kierowane są do właściwego systemu diagnostycznego...
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Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki
PublikacjaThis work is focused on an approach based on the emotional content of music and its automatic recognition. A vector of features describing emotional content of music was proposed. Additionally, a graphical model dedicated to the subjective evaluation of mood of music was created. A series of listening tests was carried out, and results were compared with automatic mood recognition employing SOM (Self Organizing Maps) and ANN (Artificial...
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Collaborative approach to WordNet and Wikipedia integration
PublikacjaIn this article we present a collaborative approach tocreating mappings between WordNet and Wikipedia. Wikipediaarticles have been first matched with WordNet synsets in anautomatic way. Then such associations have been evaluated andcomplemented in a collaborative way using a web application.We describe algorithms used for creating automatic mappingsas well as a system for their collaborative development. Theoutcome enables further...
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A fuzzy logic model for forecasting exchange rates
PublikacjaThis article is devoted to the issue of forecasting exchange rates. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology - fuzzy logic theory - and to evaluate its effectiveness in times of prosperity and during the financial crisis. The model is based on sets of rules written by the author in the form of IF-THEN, where expert knowledge is stored. This model is the result...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical 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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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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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...