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Tytuł:
A hybrid algorithm for solving inverse problems in elasticity
Autorzy:
Barabasz, B.
Gajda-Zagórska, E.
Migórski, S.
Paszyński, M.
Schaefer, R.
Smołka, M.
Powiązania:
https://bibliotekanauki.pl/articles/331427.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
inverse problem
hierarchic genetic strategy
hybrid optimization
automatic hp adaptive finite element method
zagadnienie odwrotne
strategia genetyczna
optymalizacja hybrydowa
metoda elementów skończonych
Opis:
The paper offers a new approach to handling difficult parametric inverse problems in elasticity and thermo-elasticity, formulated as global optimization ones. The proposed strategy is composed of two phases. In the first, global phase, the stochastic hp-HGS algorithm recognizes the basins of attraction of various objective minima. In the second phase, the local objective minimizers are closer approached by steepest descent processes executed singly in each basin of attraction. The proposed complex strategy is especially dedicated to ill-posed problems with multimodal objective functionals. The strategy offers comparatively low computational and memory costs resulting from a double-adaptive technique in both forward and inverse problem domains. We provide a result on the Lipschitz continuity of the objective functional composed of the elastic energy and the boundary displacement misfits with respect to the unknown constitutive parameters. It allows common scaling of the accuracy of solving forward and inverse problems, which is the core of the introduced double-adaptive technique. The capability of the proposed method of finding multiple solutions is illustrated by a computational example which consists in restoring all feasible Young modulus distributions minimizing an objective functional in a 3D domain of a photo polymer template obtained during step and flash imprint lithography.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 4; 865-886
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new auto adaptive fuzzy hybrid particle swarm optimization and genetic algorithm
Autorzy:
Dziwiński, Piotr
Bartczuk, Łukasz
Paszkowski, Józef
Powiązania:
https://bibliotekanauki.pl/articles/1837533.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
hybrid methods
Particle Swarm Optimization
Genetic Algorithm
fuzzy systems
multimodal function
Opis:
The social learning mechanism used in the Particle Swarm Optimization algorithm allows this method to converge quickly. However, it can lead to catching the swarm in the local optimum. The solution to this issue may be the use of genetic operators whose random nature allows them to leave this point. The degree of use of these operators can be controlled using a neuro-fuzzy system. Previous studies have shown that the form of fuzzy rules should be adapted to the fitness landscape of the problem. This may suggest that in the case of complex optimization problems, the use of different systems at different stages of the algorithm will allow to achieve better results. In this paper, we introduce an auto adaptation mechanism that allows to change the form of fuzzy rules when solving the optimization problem. The proposed mechanism has been tested on benchmark functions widely adapted in the literature. The results verify the effectiveness and efficiency of this solution.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 95-111
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor
Autorzy:
Knypiński, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/2204509.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid cuckoo search algorithm
heuristic algorithms
multi-objective optimization
permanent magnet synchronous motor
PMSM
algorytm kukułki hybrydowy
algorytm Cuckoo
algorytm heurystyczny
optymalizacja wielocelowa
silnik synchroniczny z magnesem trwałym
Opis:
The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144586
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system
Autorzy:
Mostafa, Hazem H.
Ibrahim, Amr M.
Anis, Wagdi R.
Powiązania:
https://bibliotekanauki.pl/articles/141645.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid optimization
golden sections search
multi-verse optimization algorithm
maximum power point tracking
perturb and observe
photovoltaic (PV)
Opis:
This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS- PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.
Źródło:
Archives of Electrical Engineering; 2019, 68, 3; 611-627
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An agent-oriented hierarchic strategy for solving inverse problems
Autorzy:
Smołka, M.
Schaefer, R.
Paszyński, M.
Pardo, D.
Álvarez-Aramberri, J.
Powiązania:
https://bibliotekanauki.pl/articles/329764.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
inverse problem
hybrid optimization method
memetic algorithm
multi-agent system
magnetotelluric data inversion
zadanie odwrotne
optymalizacja hybrydowa
algorytm memetyczny
system wieloagentowy
Opis:
The paper discusses the complex, agent-oriented hierarchic memetic strategy (HMS) dedicated to solving inverse parametric problems. The strategy goes beyond the idea of two-phase global optimization algorithms. The global search performed by a tree of dependent demes is dynamically alternated with local, steepest descent searches. The strategy offers exceptionally low computational costs, mainly because the direct solver accuracy (performed by the hp-adaptive finite element method) is dynamically adjusted for each inverse search step. The computational cost is further decreased by the strategy employed for solution inter-processing and fitness deterioration. The HMS efficiency is compared with the results of a standard evolutionary technique, as well as with the multi-start strategy on benchmarks that exhibit typical inverse problems’ difficulties. Finally, an HMS application to a real-life engineering problem leading to the identification of oil deposits by inverting magnetotelluric measurements is presented. The HMS applicability to the inversion of magnetotelluric data is also mathematically verified.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 3; 483-498
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis and optimization of hybrid renewable energy systems
Analiza i optymalizacja hybrydowego systemu bazującego na odnawialnych źródłach energii
Autorzy:
Palej, Patryk
Qusay, Hassan
Kleszcz, Sławosz
Hanus, Robert
Jaszczur, Marek
Powiązania:
https://bibliotekanauki.pl/articles/283565.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Instytut Gospodarki Surowcami Mineralnymi i Energią PAN
Tematy:
hybrid system
renewable sources of energy
energy safety
optimization
optymalizacja
odnawialne źródła energii
bezpieczeństwo energetyczne
system hybrydowy
Opis:
Hybrid Renewable Energy Systems connected to the traditional power suppliers are an interesting technological solution in the field of energy engineering and the integration of renewable systems with other energy systems can significantly increase in energy reliability. In this paper, an analysis and optimization of the hybrid energy system, which uses photovoltaic modules and wind turbines components connected to the grid, is presented. The system components are optimized using two objectives criteria: economic and environmental. The optimization has been performed based on the experimental data acquired for the whole year. Results showed the optimal configuration for the hybrid system based on economical objective, that presents the best compromise between the number of components and total efficiency. This achieved the lowest cost of energy but with relatively high CO2 emissions, while environmental objective results with lower CO2 emissions and higher cost of energy and presents the best compromise between the number of components and system net present cost. It has been shown that a hybrid system can be optimized in such a way that CO2 emission is maximally reduced and – separately – in terms of reducing the cost. However, the study shows that these two criteria cannot be optimized at the same time. Reducing the system cost increase CO2 emission and enhancing ecological effect makes the system cost larger. However, depends on strategies, a balance between different optimization criteria can be found. Regardless of the strategy used economic criteria – which also indirect takes environmental aspects as a cost of penalties – should be considered as a major criterion of optimization while the other objectives including environmental objectives are less important.
Energia elektryczna produkowana z dostępnej powszechnie energii odnawialnej ze względu na nieprzewidywalność wytwarzania ma często bardzo niską jakość. Rozwiązaniem tego problem mogą być układy hybrydowe, w których systemy bazujące na energii odnawialnej połączone zostają z tradycyjnymi systemami bazującymi na energii nieodnawialnej. Integracja takich układów może znacząco zwiększyć ich niezawodność energetyczną i poprawić jakość dostaw energii. W niniejszym artykule przedstawiono analizę oraz optymalizację hybrydowego systemu energetycznego wykorzystującego moduły fotowoltaiczne oraz turbiny wiatrowe i podłączonego do sieci elektroenergetycznej. Komponenty systemu podlegają optymalizacji przy wykorzystaniu dwóch kryteriów optymalizacyjnych: ekonomicznego i środowiskowego. Optymalizacja została przeprowadzona w oparciu o wyniki pomiarów eksperymentalnych dla całego roku. Uzyskane wyniki pozwoliły na określenie optymalnej konfiguracji systemu hybrydowego, który stanowi najlepszy kompromis między liczbą komponentów a całkowitą jego wydajnością. Wykazano, że system hybrydowy można zoptymalizować w taki sposób, aby emisja CO2 była minimalna lub w taki sposób, aby całkowity koszty systemu NPC był minimalny. Przeprowadzone analizy pokazują jednak, że tych dwóch kryteriów nie można jednocześnie zoptymalizować. Zmniejszenie emisji CO2, a tym samym zwiększenie efektu ekologicznego sprawia, że system kosztuje znacznie więcej. Niezależnie od zastosowanej strategii kryterium ekonomiczne, które pośrednio uwzględnia aspekty środowiskowe (w postaci kar lub opłat środowiskowych), powinno być traktowane jako główne kryterium optymalizacji, natomiast inne kryteria, w tym środowiskowe, należy traktować jako drugorzędne.
Źródło:
Polityka Energetyczna; 2019, 22, 2; 107-120
1429-6675
Pojawia się w:
Polityka Energetyczna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of the reliability of photovoltaic-microwind based hybrid power system with battery storage for optimized electricity generation at Tlemcen, north west Algeria
Autorzy:
Hadjidj, Mohammed Salim
Bibi-Triki, Nacereddine
Didi, Faouzi
Powiązania:
https://bibliotekanauki.pl/articles/240901.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
modeling
optimization
simulation
photovoltaic system
wind system
hybrid photovoltaic-wind-storage system
sizing
modelowanie
optymalizacja
symulacja
system fotowoltaiczny
wymiarowanie
Opis:
This article considers designing of a renewable electrical power generation system for self-contained homes away from conventional grids. A model based on a technique for the analysis and evaluation of two solar and wind energy sources, electrochemical storage and charging of a housing area is introduced into a simulation and calculation program that aims to decide, based on the optimized results, on electrical energy production system coupled or separated from the two sources mentioned above that must be able to ensure a continuous energy balance at any time of the day. Such system is the most cost-effective among the systems found. The wind system adopted in the study is of the low starting speed that meets the criteria of low winds in the selected region under study unlike the adequate solar resource, which will lead to an examination of its feasibility and profitability to compensate for the inactivity of photovoltaic panels in periods of no sunlight. That is a system with fewer photovoltaic panels and storage batteries whereby these should return a full day of autonomy. Two configurations are selected and discussed. The first is composed of photovoltaic panels and storage batteries and the other includes the addition of a wind system in combination with the photovoltaic system with storage but at a higher investment cost than the first. Consequently, this result proves that is preferable to opt for a purely photovoltaic system supported by the storage in this type of site and invalidates the interest of adding micro wind turbines adapted to sites with low wind resources.
Źródło:
Archives of Thermodynamics; 2019, 40, 1; 161-185
1231-0956
2083-6023
Pojawia się w:
Archives of Thermodynamics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Antioxidant Activity of Hybrid Sturgeon (Huso dauricus × Acipenser schrenckii) Protein Hydrolysate Prepared Using Bromelain, Its Fractions and Purified Peptides
Autorzy:
Noman, Anwar
Wang, Yuxia
Zhang, Chao
Abed, Sherif M.
Powiązania:
https://bibliotekanauki.pl/articles/2019350.pdf
Data publikacji:
2022-03-01
Wydawca:
Instytut Rozrodu Zwierząt i Badań Żywności Polskiej Akademii Nauk w Olsztynie
Tematy:
hybrid sturgeon
enzymatic hydrolysis
hydrolysis optimization
bromelain
degree of hydrolysis
radical scavenging activity
peptide purification
Opis:
Protein hydrolysates could be a natural and safer source of antioxidant peptides. The purpose of this study was to optimize the hydrolysis of Huso dauricus × Acipenser schrenckii sturgeon proteins using bromelain and purify antioxidant peptides from hydrolysate. The degree of hydrolysis of 18.69% was obtained under the optimal conditions and hydrolysate had 94.76% solubility, 902 nm particle size and high antioxidant activity. The IC50 for DPPH• and ABTS•+ scavenging activity were 3.14 and 3.81 mg/mL, respectively. The fraction of hydrolysate with a molecular weight of <1 kDa exhibited the highest antiradical activity against DPPH• with IC50 of 2.10 mg/mL. In turn, the IC50 of the most active fraction after the Sephadex G-15 separation was 1.77 mg/mL. The reverse phase high performance liquid chromatography (RP-HPLC) was used to purify the peptides from this fraction. The peptide with histidine, leucine and glycine (MW of 0.2955 kDa) exhibited the highest antioxidant activity (IC50 of 1.33 mg/mL). The obtained fractions and peptides with antioxidant activity could be used as natural substitutes for synthetic antioxidants, especially in food and pharmaceuticals.
Źródło:
Polish Journal of Food and Nutrition Sciences; 2022, 72, 1; 79-89
1230-0322
2083-6007
Pojawia się w:
Polish Journal of Food and Nutrition Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cellular particle swarm optimization with a simple adaptive local search strategy for the permutation flow shop scheduling problem
Autorzy:
Seck-Tuoh-Mora, Juan C.
Medina-Marin, Joselito
Martinez-Gomez, Erick S.
Hernandez-Gress, Eva S.
Hernandez-Romero, Norberto
Volpi-Leon, Valeria
Powiązania:
https://bibliotekanauki.pl/articles/230060.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
flow shop
particle swarm optimization (PSO)
local search strategy
hybrid search method
cellular automata
scheduling
Opis:
Permutation flow shop scheduling problem deals with the production planning of a number of jobs processed by a set of machines in the same order. Several metaheuristics have been proposed for minimizing the makespan of this problem. Taking as basis the previous Alternate Two-Phase PSO (ATPPSO) method and the neighborhood concepts of the Cellular PSO algorithm proposed for continuous problems, this paper proposes the improvement of ATPPSO with a simple adaptive local search strategy (called CAPSO-SALS) to enhance its performance. CAPSO-SALS keeps the simplicity of ATPPSO and boosts the local search based on a neighborhood for every solution. Neighbors are produced by interchanges or insertions of jobs which are selected by a linear roulette scheme depending of the makespan of the best personal positions. The performance of CAPSO-SALS is evaluated using the 12 different sets of Taillard’s benchmark problems and then is contrasted with the original and another previous enhancement of the ATPPSO algorithm. Finally, CAPSO-SALS is compared as well with other ten classic and state-of-art metaheuristics, obtaining satisfactory results.
Źródło:
Archives of Control Sciences; 2019, 29, 2; 205-226
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Combining Rough Sets and Neural Network Approaches in Pattern Recognition
Autorzy:
Cyran, K.
Powiązania:
https://bibliotekanauki.pl/articles/92799.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
pattern recognition
neural networks
rough sets
hybrid methods
evolutionary optimization
holographic ring-wedge detector
Opis:
The paper focuses on problems which arise when two different types of AI methods are combined in one design. The first type is rule based, rough set methodology operating is highly discretized attribute space. The discretization is a consequence of the granular nature of knowledge representation in the theory of rough sets. The second type is neural network working in continuous space. Problems of combining these different types of knowledge processing are illustrated in a system used for recognition of diffraction patterns. The feature extraction is performed with the use of holographic ring wedge detector, generating the continuous feature space. No doubt, this is a feature space natural for application of the neural network. However, the criterion of optimization of the feature extractor uses rough set based knowledge representation. This latter, requires the discretization of conditional attributes generating the feature space. The novel enhanced method of optimization of holographic ring wedge detector is proposed, as a result of modification of indiscernibility relation in the theory of rough sets.
Źródło:
Studia Informatica : systems and information technology; 2005, 2(6); 7-20
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Study of Particle Swarm Optimization and Genetic Algorithms for Complex Mathematical Functions
Autorzy:
Valdez, F.
Melin, P.
Powiązania:
https://bibliotekanauki.pl/articles/384575.pdf
Data publikacji:
2008
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
genetic algorithms
particle swarm optimization (PSO)
hybrid systems
optimization
Opis:
The Particle Swarm Optimization (PSO) and the Genetic Algorithms (GA) have been used successfully in solving problems of optimization with continuous and combinatorial search spaces. In this paper the results of the application of PSO and GAs for the optimization of mathematical functions are presented. These two methodologies have been implemented with the goal of making a comparison of their performance in solving complex optimization problems. This paper describes a comparison between a GA and PSO for the optimization of complex mathematical functions.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 1; 43-51
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effectiveness of hybrid optimization methods in solving test problems and practical issues
Autorzy:
Twardochleb, Michał
Król, Tomasz
Włoch, Paweł
Kuka, Bartosz
Powiązania:
https://bibliotekanauki.pl/articles/431905.pdf
Data publikacji:
2013
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
hybrid
optimization
decision problem
Opis:
This paper shows the results of analyzing the effectiveness and efficiency of a hybrid approach against a variety of optimization problems. An application with a serial-optimization structure, consisting of several methods with different characteristics, is presented. In order to evaluate the initial effectiveness of the hybrid optimization method, a number of test tasks, represented by complex functions with many variables, were examined. Additionally, a real-life case, determining an optimal product variety in a supermarket environment, regarding the highest rate of return for given conditions and limitations, is presented as an instance of the practical use of a hybrid algorithm. The research shows that the results achieved by the hybrid- -optimization method are highly satisfactory, both in terms of efficiency as well as effectiveness.
Źródło:
Informatyka Ekonomiczna; 2013, 4(30); 279-289
1507-3858
Pojawia się w:
Informatyka Ekonomiczna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary computation based on Bayesian classifiers
Autorzy:
Miquelez, T.
Bengoetxea, E.
Larranaga, P.
Powiązania:
https://bibliotekanauki.pl/articles/907630.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
rozumowanie probabilistyczne
obliczenia ewolucyjne
sieć Bayesa
estymacja algorytmu dystrybucji
hybrid soft computing
probabilistic reasoning
evolutionary computing
classification
optimization
Bayesian networks
estimation of distribution algorithms
Opis:
Evolutionary computation is a discipline that has been emerging for at least 40 or 50 years. All methods within this discipline are characterized by maintaining a set of possible solutions (individuals) to make them successively evolve to fitter solutions generation after generation. Examples of evolutionary computation paradigms are the broadly known Genetic Algorithms (GAs) and Estimation of Distribution Algorithms (EDAs). This paper contributes to the further development of this discipline by introducing a new evolutionary computation method based on the learning and later simulation of a Bayesian classifier in every generation. In the method we propose, at each iteration the selected group of individuals of the population is divided into different classes depending on their respective fitness value. Afterwards, a Bayesian classifier---either naive Bayes, seminaive Bayes, tree augmented naive Bayes or a similar one---is learned to model the corresponding supervised classification problem. The simulation of the latter Bayesian classifier provides individuals that form the next generation. Experimental results are presented to compare the performance of this new method with different types of EDAs and GAs. The problems chosen for this purpose are combinatorial optimization problems which are commonly used in the literature.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2004, 14, 3; 335-349
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid approach to supporting decision making processes in companies
Autorzy:
Pietruszkiewicz, W.
Twardochleb, M.
Roszkowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/205657.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
data mining
cascade optimization hybrid
parallel classification hybrid
hybrid multicomponent attribute selection
Opis:
This article presents the advantages of hybrid approach to the support decision making by analyzing three areas of business decision problems, solved by combination of well-known algorithms into the new hybrid constructions: cascade optimization hybrid, parallel classification hybrid and hybrid multicomponent attribute selection. Each of them solved a different problem: the cascade optimization hybrid allowed for finding an extreme of a composite objective function, the parallel classification hybrid was used to choose a proper class through voting, the multicomponent attribute selection robustly chose significant decision variables. A hybrid approach to the problem of supporting the decision making processes is more effective than using each of the component methods alone, even for the sophisticated ones. A combination of several methods with different characteristics and performance makes it possible to take advantages of their strong sides and simultaneously eliminate the weak ones, resulting in a better computational support of decision making.
Źródło:
Control and Cybernetics; 2011, 40, 1; 125-143
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid energy system - optomization and new concept
Hybrydowy system energetyczny - nowa koncepcja i optymalizacja
Autorzy:
Moravek, J.
Mastny, P.
Powiązania:
https://bibliotekanauki.pl/articles/408282.pdf
Data publikacji:
2014
Wydawca:
Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:
hybrid energy system
MATLAB simulation
optimization
hybrydowy system energetyczny
symulacja w MATLAB-ie
optymalizacja
Opis:
Paper presents a research related to the design of a new concept of hybrid energy system. It describes actually used concepts and the benefits of new design. Subsequently, the problems of the proper systems setting and working conditions are discussed and the new concept of the systems settings is presented. Research is further enhanced by comparing with the simulation model assuming the weather data acquired for the test location. The measured data are compared with the results of simulation.
Artykuł przedstawia projekt nowej koncepcji hybrydowego systemu energetycznego. W pracy przedstawiono aktualnie stosowane koncepcje i na ich tle zalety nowego podejścia. Następnie dyskutowano odpowiednie ustawienia i warunki pracy systemu oraz przedstawiono nową koncepcję systemu. Dodatkowo badania są zilustrowane porównaniem z modelem symulacyjnym, przy założeniu, że dane pogodowe pozyskane zostały dla testowej lokalizacji.
Źródło:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2014, 3; 77-80
2083-0157
2391-6761
Pojawia się w:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 29

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