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Wyniki wyszukiwania dla: deep learning, genetic algorithm, artificial neural networks, predictive maintenance, cost efficient maintenance
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Genetic features of clinical Pseudomonas aeruginosa strains
PublikacjaW grupie 62 izolatów klinicznych sprawdzono obecność 6 wybranych czynnikow wirulencji. We wcześniejszych badaniach z wykorzystaniem techniki ERIC - PCR wykazano, że w analizowanej grupie 49 (79%) to szczepy, o dużum podobieństwie genetycznym (ponad 62%), każdy z pozostałych 13 izolatów zaliczono do osobnego genotypu, o zdecydownie niższym stopniu pokrewieństwa. W przypadku wszystkich 49 szczepów z pierwszej grupy stwierdzono obecność...
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FPGA realization of an improved alpha max plus beta min algorithm
PublikacjaThe generalized improved version of the alpha max plus beta min square-rooting algorithm and its realization in the Field Programmable Gate Array (FPGA) are presented. The algorithm computes the square root to calculate the approximate magnitude of a complex sample. It is especially useful for pipelined calculations in the DSP. In case of four approximation regions it is possible to reduce the peak error form 3.95% to 0.33%. This...
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Improving SBR Performance Alongside with Cost Reduction through Optimizing Biological Processes and Dissolved Oxygen Concentration Trajectory
PublikacjaAuthors of this paper take under investigation the optimization of biological processes during the wastewater treatment in sequencing batch reactor (SBR) plant. A designed optimizing supervisory controller generates the dissolved oxygen (DO) trajectory for the lower level parts of the hierarchical control system. Proper adjustment of this element has an essential impact on the efficiency of the wastewater treatment process as well...
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The impact of the shape of deep drilled well screen openings on the filtration process in full saturation conditions
PublikacjaThe authors propose a supplementary method of modelling seepage flow around the deep drilled well screen. The study applies 3D numerical modelling (FEM) in order to provide an in-depth analysis of the seepage process. The analysis of filtration parameters (flow distribution q(x,t) and pressure distribution p) was conducted using the ZSoil.PC software system. The analysis indicates that the shape of perforation is of secondary importance...
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Application of spatial neural simulators of turbine blade rows to fluid flow diagnostics
PublikacjaThis chapter presents the results of neural modelling of fluid flow in steam turbine row. In modelling working conditions of the flow channel varied, thus the aim of the work was to reconstruct the reference state - distributions of velocity, pressure, and losses in flow channel - with high accuracy for fluid flow diagnostics.
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Disaster Resilience of Optical Networks: State of the Art, Challenges, and Opportunities
PublikacjaFor several decades, optical networks, due to their high capacity and long-distance transmission range, have been used as the major communication technology to serve network traffic, especially in the core and metro segments of communication networks. Unfortunately, our society has often experienced how the correct functioning of these critical infrastructures can be substantially hindered by massive failures triggered by natural...
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Arc-length Algorithm Efficiency in the Analysis of Thermally Loaded Multilayered Shells
PublikacjaThis paper concerns the efficiency study of the arc-length algorithm in the geometrically non-linear analysis of thermally loaded multilayered shells. The thermal loading is considered as the one-way thermo-mechanical coupling effect. Two implementations of the arc-length method are examined: the path-following technique available in NX-Nastran and the RiksWempner-Ramm algorithm adopted in the authors’ computer code SHLTH. It is...
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublikacjaFast replacement models have been playing an increasing role in high-frequency electronics, including the design of antenna structures. Their role is to improve computational efficiency of the procedures that normally entail large numbers of expensive full-wave electromagnetic (EM) simulations, e.g., parametric optimization or uncertainty quantification. Recently introduced performance-driven modeling methods, such as the nested...
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Predictive control of active filter system with LCL coupling circuit
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Sensorless predictive control of three-phase parallel active filter
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Analytical design of stable delta-domain generalized predictive control
PublikacjaPraca dotyczy analitycznej metody projektowania układów sterowania skalarnymi (SISO) obiektami czasu ciągłego według strategii uogólnionego sterowania predykcyjnego (GPC) w oparciu o dyskretnoczasowe modele takich obiektów. Założono wykorzystanie numeryczne odpornych modeli opartych o tak zwany operator delta. Przyjmując kwadratowy funkcjonał kosztów, w którym prognozowany przebieg przyszłego wyjścia sterowanego obiektu porównywany...
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublikacjaThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublikacjaW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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A Survey of Fast-Recovery Mechanisms in Packet-Switched Networks
PublikacjaIn order to meet their stringent dependability requirements, most modern packet-switched communication networks support fast-recovery mechanisms in the data plane. While reactions to failures in the data plane can be significantly faster compared to control plane mechanisms, implementing fast recovery in the data plane is challenging, and has recently received much attention in the literature. This survey presents a systematic,...
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Convenient and Efficient Diastereoselective Preparation of Functionalized Z -Alkenyl Sulfides
PublikacjaWe have developed an efficient and convenient regio‐ and stereoselective reduction of the alkynyl sulfides with pinacolborane in the presence of copper(I) chloride to produce (Z)‐alkenyl sulfides in good and very good yields. The functionalized alkynyl sulfides are readily available based on the reaction of lithium acetylides with thiotosylates under mild conditions.
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Performance Evaluation of Preemption Algorithms in MPLS Networks
PublikacjaPreemption is a traffic engineering technique in Multiprotocol Switching Networks that enables creation of high priority paths when there is not enough free bandwidth left on the route. Challenging part of any preemption method is to select the best set of paths for removal. Several heuristic methods are available but no wider comparison had been published before. In this paper, we discuss the dilemmas in implementing preemption...
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Performance evaluation of the parallel object tracking algorithm employing the particle filter
PublikacjaAn algorithm based on particle filters is employed to track moving objects in video streams from fixed and non-fixed cameras. Particle weighting is based on color histograms computed in the iHLS color space. Particle computations are parallelized with CUDA framework. The algorithm was tested on various GPU devices: a desktop GPU card, a mobile chipset and two embedded GPU platforms. The processing speed depending on the number...
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A 27/26-approximation algorithm for the chromatic sum coloring of bipartitegraphs
PublikacjaWe consider the CHROMATIC SUM PROBLEM on bipartite graphs which appears to be much harder than the classical CHROMATIC NUMBER PROBLEM. We prove that the CHROMATIC SUM PROBLEM is NP-complete on planar bipartite graphs with Delta less than or equal to 5, but polynomial on bipartite graphs with Delta less than or equal to 3, for which we construct an O(n(2))-time algorithm. Hence, we tighten the borderline of intractability for this...
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The searchlight problem for road networks
PublikacjaWe consider the problem of searching for a mobile intruder hiding in a road network given as the union of two or more lines, or two or more line segments, in the plane. Some of the intersections of the road network are occupied by stationary guards equipped with a number of searchlights, each of which can emit a single ray of light in any direction along the lines (or line segments) it is on. The goal is to detect the intruder,...
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COMPARISON OF SOFTWARE AND HARDWARE REALIZATION OF AES CRYPTOGRAPHIC ALGORITHM
PublikacjaIn this paper hardware and software realization of direct and inverse AES cryptographic algorithm is presented. Both implementations were made using the Virtex-II FPGA and were practically tested. As the criteria of comparison, the resource utilization, achieved performance and power dissipation were chosen. Hardware realization increases throughput of conversion about 190 times over software implementation and decreases the energy...
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EPILEPTIC BEHAVIOR WITH A DISTINGUISHED PREICTAL PERIOD IN A LARGE-SCALE NEURAL NETWORK MODEL
PublikacjaWe present a neural network model capable of reproducing focal epileptic behavior. An important property of our model is the distinguished preictal state. This novel feature may shed light on the pathologi-cal mechanisms of seizure generation and, in perspective, help develop new therapeutic strategies to manage refractory partial epilepsy.
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublikacjaA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublikacjaPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
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Convenient and efficient synthesis of functionalized unsymmetrical Z-alkenyl disulfanes
PublikacjaWe developed a simple and efficient method for the synthesis of functionalized unsymmetrical Z-alkenyl disulfanes under mild conditions in moderate to good yields. The designed method is based on the reaction of Z-alkenyl thiotosylates with thiols in the presence of base. The developed method allows the preparation of unsymmetrical Z-alkenyl disulfanes bearing additional hydroxy, carboxy, or amino functionalities.
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Buck-Boost Inverters with Symmetrical Passive Four-terminal Networks
PublikacjaAlternating Voltage Inverters (Converters) supplied by low-voltage sources DC (ex. fuel cell, photovoltaic cell) are most frequently realized on the basis of the three fundamental topologies: a) PWM voltage inverter with boost-converter" system, b) PWM voltage inverter with transformed converter DC/DC in the ,,boost-converter" system, c) PWM current converter. However none of these solutions is claimed to be the best and dominant...
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Effects of safety barrier life cycle cost factors - identification and analysis
PublikacjaThe costs borne by road infrastructure authorities for managing and maintaining road devices such as safety barriers may be very high. This has prompted the need for identifying and analysing in detail all factors that influence the costs of safety barriers throughout their service life. To meet that need, the authors used international experience and field data collected under the LifeRoSE project to define the cost structure...
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A robust optimization model for affine/quadratic flow thinning: A traffic protection mechanism for networks with variable link capacity
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublikacjaGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
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Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization
PublikacjaIn order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation...
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Enhancing Performance of Switched Parasitic Antenna for Localization in Wireless Sensor Networks
PublikacjaThis paper presents an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). The limitations of the existing design approach are illustrated, as well as perspectives and challenges of the proposed solution in relation to the localization in...
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublikacjaThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublikacjaIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
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Digits Recognition with Quadrant Photodiode and Convolutional Neural Network
PublikacjaIn this paper we have investigated the capabilities of a quadrant photodiode based gesture sensor in the recognition of digits drawn in the air. The sensor consisting of 4 active elements, 4 LEDs and a pinhole was considered as input interface for both discrete and continuous gestures. Index finger and a round pointer were used as navigating mediums for the sensor. Experiments performed with 5 volunteers...
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An Algorithm for Listing All Minimal 2-Dominating Sets of a Tree
PublikacjaWe provide an algorithm for listing all minimal 2-dominating sets of a tree of order n in time O(1.3248n) . This implies that every tree has at most 1.3248 n minimal 2-dominating sets. We also show that this bound is tigh.
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Distributed measurement system with data transmission secured using XXTEA algorithm
PublikacjaThe paper deals with wireless data transmission security in the distributed measurement and control system. An overview of cryptographic algorithms was presented paying special attention to the algorithm dedicated to units with low processing power, which is important due to minimization of energy consumption. Measurement modules equipped with simple microcontrollers send data wirelessly to the central unit. The transmission was...
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Enhancing environmental literacy through urban technology- based learning. The PULA app casebased learning. The PULA app case
PublikacjaThis study addresses the need to enhance environmental literacy, focusing on urban adults through mobile applications, based on the example of PULA app that engages early adopters in gamified pro- environmental activities, offering insights into informal learning. Grounded in 'urban pedagogy,' the study combines semi-structured interviews with 17 application testers and quantitative data analysis, unveiling motivations, user feedback,...
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Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublikacjaIn this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...
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Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublikacjaABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
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Artificial intelligence and productivity: global evidence from AI patent and bibliometric data
PublikacjaIn this paper we analyse the relationship between technological innovation in the artificial intelligence (AI) domain and macroeconomic productivity. We embed recently released data on patents and publications related to AI in an augmented model of productivity growth, which we estimate for the OECD countries and compare to an extended sample including non-OECD countries. Our estimates provide evidence in favour of the modern productivity...
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An algorithm for listing all minimal double dominating sets of a tree
PublikacjaWe provide an algorithm for listing all minimal double dominating sets of a tree of order $n$ in time $\mathcal{O}(1.3248^n)$. This implies that every tree has at most $1.3248^n$ minimal double dominating sets. We also show that this bound is tight.
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Functional safety in the context of risk appraisal criteria and cost-benefit analysis
PublikacjaRozdział przedstawia aktualne zagadnienia dotyczące analizy kosztów i efektów rozwiązań związanych z bezpieczeństwem na przykładzie systemów elektrycznych, elektronicznych i programowalnych elektronicznych (E/E/PE) pełniących funkcje sterowania i zabezpieczeń w obiektach podwyższonego ryzyka. Podkreśla się znaczenie kryteriów związanych z bezpieczeństwem, takich jak tolerowalność ryzyka (TOR) w kontekście analizy kosztów i efektów...
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublikacjaContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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Improving Clairvoyant: reduction algorithm resilient to imbalanced process arrival patterns
PublikacjaThe Clairvoyant algorithm proposed in “A novel MPI reduction algorithm resilient to imbalances in process arrival times” was analyzed, commented and improved. The comments concern handling certain edge cases in the original pseudocode and description, i.e., adding another state of a process, improved cache friendliness more precise complexity estimations and some other issues improving the robustness of the algorithm implementation....
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A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds
PublikacjaThe recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublikacjaIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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Relationship between Telomere Length, TERT Genetic Variability and TERT, TP53, SP1, MYC Gene Co-Expression in the Clinicopathological Profile of Breast Cancer
PublikacjaThe molecular mechanisms of telomerase reverse transcriptase (TERT) upregulation in breast cancer (BC) are complex. We compared genetic variability within TERT and telomere length with the clinical data of patients with BC. Additionally, we assessed the expression of the TERT, MYC, TP53 and SP1 genes in BC patients and in BC organoids (3D cell cultures obtained from breast cancer tissues). We observed the same correlation in the...
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The influence of pressure drop on the working volume of a hydraulic motor
PublikacjaReliability and maintenance analysis of hydraulic positive machines basicly focused on the processes of their wear and failure. But in order to correctly assess the mechanical and volumetric efficiency of a hydraulic motor, both at the stage of development research or at the stage of control tests during its exploitation, the working volume of this motor must be correctly determined. Therefore this paper proposes a new method of...
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Monitoring the gas turbine start-up phase on the platform using a hierarchical model based on Multi-Layer Perceptron networks
PublikacjaVery often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition...