Wyniki wyszukiwania - Biblioteka Nauki

1

Hybrid modeling of biomedical systems and measuring nonlinear characteristics of biosignals for improving quality of life

100%

Darowski M. , Klonowski W. , Kozarski M. , Ferrari G. , Zieliński K. , Stępień R.

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tom Vol. 14, nr 1

89-100

EN

The main purpose of this paper is to present some metrological aspects of the new concept of hybrid modeling (combined physical and in silico) of biological systems as well as possible applications of nonlinear (symbolic) biosignal analysis for improving quality of life through modeling and knowledge-based measurements in medicine.

2

Możliwe struktury systemów hybrydowych w przetwarzaniu informacji nieprecyzyjnych dla rozwiązywania wieloaspektowych problemów optymalnego zużycia wody do nawadniania roślin

86%

Baranowska E.

Journal of Research and Applications in Agricultural Engineering

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2012

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tom Vol. 57, nr 1

5-8

PL

Dążenie ludzi nauki do uzyskania coraz większego uproszczenia struktury modeli, a jednocześnie do coraz większej dokładności i wymiarowości, przynosi rezultaty w postaci tworzenia nowych modeli. Modelowanie ma zasadnicze znaczenie w działalności naukowej i inżynierskiej. Efektywne funkcjonowanie istniejących systemów nawadniania zależy od dokładności i precyzji modelowania. Przedsięwzięcie wielokierunkowe, jakim jest proces modelowania dla potrzeb inżynierii rolniczej wymaga połączenia wiedzy z różnych dyscyplin przyrodniczych: agrometeorologii, agrofizyki, gleboznawstwa, fizjologii roślin, uprawy roślin i wielu innych. Także wymaga interdyscyplinarnych zespołów badawczych. Wiodącym czynnikiem podnoszącym efektywność modelowania jest implementacja do istniejących modeli symulacyjnych pozyskanych za pomocą odpowiednich technik informacji. Ma to na celu minimalizację błędów symulacji. W pracy przedstawiono poglądowy zarys systemów hybrydowych.

EN

The desire of scientists to obtain an ever increasing simplification of the structure of models, whilst increasing the accuracy and dimensionality results in the creation of new models. Modeling is crucial in research and engineering. The efficient functioning of the existing irrigation systems depends on modeling accuracy and precision. The project which is a multidirection modeling process for agricultural engineering purposes requires a combination of knowledge from different disciplines of natural sciences: agrometeorology, agrophysics, soil science, plant physiology, cultivation and many others also requires interdisciplinary research teams. The leading factor in increasing the efficiency of modeling is to implement the existing simulation models obtained using the corresponding techniques of information. The aim is to minimize the minimize the errors of the simulation. The paper presents a pictorial overview of hybrid systems.

3

Research on speed control of high speed trains based on hybrid modeling

72%

Hou T. , Tang L. , Niu H.-x. , Zhao T.

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tom Vol. 66, iss. 2

77--82

EN

With the continuous improvement of train speed, the automatic driving of trains instead of driver driving has become the development direction of rail transit in order to realize traffic automation. The application of single modeling methods for speed control in the automatic operation of high-speed trains lacks exploration of the combination of train operation data information and physical model, resulting in low system modeling accuracy, which impacts the effectiveness of speed control and the operation of high-speed trains. To further increase the dynamic modeling accuracy of high-speed train operation and the high-speed train's speed control effect, a high-speed train speed control method based on hybrid modeling of mechanism and data drive is put forward. Firstly, a model of the high-speed train's mechanism was created by analyzing the train's dynamics. Secondly, the improved kernel-principal component regression algorithm was used to create a data-driven model using the actual operation data of the CRH3 (China Railway High-speed 3) high-speed train from Huashan North Railway Station to Xi'an North Railway Station of "Zhengxi High-speed Railway," completing the mechanism model compensation and the error correction of the speed of the actual operation process of the high-speed train, and realizing the hybrid modeling of mechanism and data-driven. Finally, the prediction Fuzzy PID control algorithm was developed based on the natural line and train characteristics to complete the train speed control simulation under the hybrid model and the mechanism model, respectively. In addition, analysis and comparison analysis were conducted. The results indicate that, compared to the high-speed train speed control based on the mechanism model, the high-speed train speed control based on hybrid modeling is more accurate, with an average speed control error reduced by 69.42%. This can effectively reduce the speed control error, improve the speed control effect and operation efficiency, and demonstrate the efficacy of the hybrid modeling and algorithm. The research results can provide a new ideal of multi-model fusion modeling for the dynamic modeling of high-speed train operation, further improve control objectives such as safety, comfort, and efficiency of high-speed train operation, and provide a reference for automatic driving and intelligent driving of high-speed trains.

4

Application of constraint logic programming to decision support for the supply chain management

72%

Sitek P.

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2013

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tom R. 17, nr 2

129-134

EN

Supply Chain Management (SCM) decisions can be considered at different levels of detail. At a strategic level they apply to the architecture in the supply chain, at the tactical level to transport fleet selection, selection of supply sources and distribution, and at the operational level, to the distribution of supplies and route selection. Many models of decision-making SCM have been developed. These are the linear (LP-linear programming) or mixed (MIP/MILP-Mixed Integer/Linear Integer Programming) models. These models are equipped with a smart form. Although they are well known in the OR (Operation Research) environment, they have significant drawbacks. First of all, they must support only linear constraints. For problems of larger dimensions search for solutions is long and inefficient. This paper proposes a CSP-based decision model for SCM and its implementation in the CLP (Constraint Logic Programming). In addition, it presents a novel way of constraints propagation using the structure of the problem.

PL

Decyzje w zarządzaniu łańcuchem dostaw mogą być rozpatrywane na różnych poziomach szczegółowości. Na poziomie strategicznym dotyczą samej struktury i architektury łańcucha, na poziomie taktycznym wyboru floty transportowej, a na poziomie operacyjnym wyboru tras dostaw itd. Opracowano wiele formalnych modeli zarządzania łańcuchem dostaw. Najczęściej były to modele programowania matematycznego liniowego (LP) oraz całkowitoliczbowego (MILP). Chociaż posiadały struktury dobrze rozumiane w środowiskach (OR-Badań Operacyjnych), posiadały istotne wady. Po pierwsze, mogły zawierać jedynie ograniczenia liniowe. Po drugie nie były efektywne przy większych rozmiarach problemów decyzyjnych. W Artykule zaproponowano model decyzyjny dla łańcucha dostaw oparty na problemie spełnienia ograniczeń (CSP-based) oraz jego implementacji w środowisku programowania w logice z ograniczeniami (CLP). Dodatkowo zaprezentowano nowatorski sposób propagacji ograniczeń wykorzystujący strukturę problemu.