The main goal of our research is to build the ontology of places in Poland covering a variety of aspects of places, mainly administrative and socio-economic. The ontology is being implemented using the OWL 2 Web Ontol...
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The main goal of our research is to build the ontology of places in Poland covering a variety of aspects of places, mainly administrative and socio-economic. The ontology is being implemented using the OWL 2 Web Ontology Language. In the created OWL ontology, we can distinguish two kinds of classes, primary classes exactly defined in the ontology as well as secondary classes defined over the ontology on the basis of primary classes and properties of individuals considered in the ontology. We show how to use rough sets to approximate secondary classes by means of primary classes in the created ontology. Rough set approximations enable us to extract some useful knowledge about places.
The axle temperature of the high speed train is the most direct reflection of the train operating conditions while it is also affected by many factors. The factors which significantly affect the axle temperature are s...
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ISBN:
(纸本)9781509048410
The axle temperature of the high speed train is the most direct reflection of the train operating conditions while it is also affected by many factors. The factors which significantly affect the axle temperature are screened out by using the stepwise regression analysis and the prediction equation of the axle temperature is established, so as to compare the predicted data and the measured data. The validity of the coefficients in the equation is verified through R-squared, F test and T test. The experiment shows that R-squared is between 0.81 and 0.93, indicating a high degree of fitting prediction equations, and F test results show that the overall equation is significantly better. The results of T test indicate that the velocity, the carrying capability and the ambient temperature have significant influence on the change of axle temperature. But the traction and the power of traction have less effect. The result shows that this method can reflects the variation trend of axle temperature, which can provide support to the operation and maintenance of axle.
The certainty-equivalence super-twisting controller (CESTA) combines approaches from variable structure and adaptive control. In this paper, an improved variant of this algorithm is presented that resorts to a recentl...
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The certainty-equivalence super-twisting controller (CESTA) combines approaches from variable structure and adaptive control. In this paper, an improved variant of this algorithm is presented that resorts to a recently introduced Lyapunov function for the super twisting algorithm, establishing a novel continuous adaptation law. These controllers are beneficial for systems that are affected by structured and unstructured uncertainties. It is demonstrated that the combination of sliding-mode and adaptive control methodologies allows to relax the boundedness condition, known from the super twisting algorithm. In comparison to earlier work, asymptotic stability of the system states may be shown while requiring relaxed conditions on the structured uncertainty. The effectiveness of the proposed algorithm is shown with a simulation example.
There was a mistake in the grant number used in the recently published paper (DOI: https://***/10.1515/ nanoph-2019-0112. Published Online: 2019-07-09). The text should read: A.K. is grateful for support via the Russi...
The transition between the power market competition and these emerging renewable power system alternatives (wind turbines, solar plants, micro-turbine), has awaken a great deal of interest for distributed power genera...
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Hot compression of the ZnCu2A110 alloy was conducted on a Gleeble-3800D thermomechanical simulator in the temperature range of 150-330°C and strain rate of 0.01-10 s-1. Base on the experimental results, An Artifi...
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ISBN:
(纸本)9781119225836
Hot compression of the ZnCu2A110 alloy was conducted on a Gleeble-3800D thermomechanical simulator in the temperature range of 150-330°C and strain rate of 0.01-10 s-1. Base on the experimental results, An Artificial Neural Network (ANN) with double bidden layers composing of 10 neurons and 15 neurons were employed to simulate the flow behavior. The inputs of the model are temperature, strain and strain rate. The output of the model is the flow stress. As a result, the minimum relative error is 0.01%, the maximum relative error is 2.25%, and error majority concentrate within 0.81%, Mean Absolute Percentage Error (MAPE) is 0.0101, error is very small. The results indicate that the trained ANN model is a robust tool to predict the high temperature flow behavior of ZnCu2A110 alloy.
This paper presents a model predictive control (MPC) of five-level H-bridge neutral-point-clamped (NPC) quasi-impedance source inverter (qZSI). The proposed control technique is designed to handle three control object...
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This paper presents a model predictive control (MPC) of five-level H-bridge neutral-point-clamped (NPC) quasi-impedance source inverter (qZSI). The proposed control technique is designed to handle three control objectives with simple and effective approach. The output current, the input current and the capacitor voltage are the control objectives of the proposed MPC algorithm. To fulfill these control objectives, multi-objective based cost function is employed. Furthermore, qZSI has been combined with the 5-Level H-bridge NPC inverter so as to obtain power converter topology with buck/boost and dc/ac conversion functionality in a single stage for high power PV applications. Simulation results verify the proposed multi-objective MPC algorithm and inverter topology.
A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most...
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A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most of the existing recommender systems, only the purchase information is utilized data and the navigational and behavioral data are seldom concerned. In this paper, we design a novel recommender system for comprehensive online shopping sites. In the proposed recommender system, the navigational and behavioral data, such as access, click, read, and purchase information of a customer, are utilized to calculate the preference degree to each item; then items with larger preference degrees are recommended to the customer. The proposed method has several innovations and two of them are more remarkable: one is that nonexpendable items are distinguished from expendable ones and handled by a different way; another is that the interest shifting of customers are considered. Lastly, we structure an example to show the operation procedure and the performance of the proposed recommender system. The results show that the proposed recommender method with considering interest shifting is superior to Kim et al(2011) method and the method without considering interest shifting.
The paper is focused on systems with delay terms at the left (and the right) side of differential equations. Analysis and synthesis of delay systems can be conveniently studied through a special ring of RQ-meromorphic...
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ISBN:
(纸本)9781509017393
The paper is focused on systems with delay terms at the left (and the right) side of differential equations. Analysis and synthesis of delay systems can be conveniently studied through a special ring of RQ-meromorphic functions. The control methodology is based on a solution of Diophantine equations in this ring. Final controllers result in the Smith predictor like structure. Controller parameters are tuned through a pole-placement problem as a desired multiple root of the characteristic closed loop equation. The methodology is illustrated by a stable second order transfer function with a dead-time term. Then the paper brings an autotuning method as a combination of biased-relay feedback estimation and the proposed algebraic control design. The developed approach is illustrated by examples in the Matlab and Simulink environment.
Complex engineering problems require simulations, which are computationally expensive in cases of inverse identification tasks since they commonly requires hundreds of thousands of simulations. This paper propose a me...
Complex engineering problems require simulations, which are computationally expensive in cases of inverse identification tasks since they commonly requires hundreds of thousands of simulations. This paper propose a method based on model reduction for crack size estimation, combining the proper orthogonal decomposition method with radial basis functions. The reduced model is validated by comparing the obtained boundary displacements with the corresponding results from a finite element model. This inverse procedure is formulated as the minimization of the difference between the measured and computed values of displacement at selected boundary nodes, called sensor points, using particle swarm optimization algorithm. Convex and a non-convex specimens have been considered for investigations of crack presence, and identification of its size, different crack sizes have been tested to demonstrate the efficiency of the proposed approach.
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