Auswahl der wissenschaftlichen Literatur zum Thema „Methods of problem solving“

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Zeitschriftenartikel zum Thema "Methods of problem solving"

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BENJAMINS, V. RICHARD, und DIETER FENSEL. „Editorial: problem-solving methods“. International Journal of Human-Computer Studies 49, Nr. 4 (Oktober 1998): 305–13. http://dx.doi.org/10.1006/ijhc.1998.0208.

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FENSEL, DIETER, und ARNO SCH Ö. „Inverse verification of problem-solving methods“. International Journal of Human-Computer Studies 49, Nr. 4 (Oktober 1998): 339–61. http://dx.doi.org/10.1006/ijhc.1998.0210.

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Fensel, D., und E. Motta. „Structured development of problem solving methods“. IEEE Transactions on Knowledge and Data Engineering 13, Nr. 6 (2001): 913–32. http://dx.doi.org/10.1109/69.971187.

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Antonietti, Alessandro, Sabrina Ignazi und Patrizia Perego. „Metacognitive knowledge about problem-solving methods“. British Journal of Educational Psychology 70, Nr. 1 (März 2000): 1–16. http://dx.doi.org/10.1348/000709900157921.

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Golichev, Iosif Iosifovich, Timur Rafailevich Sharipov und Natal'ya Iosifovna Luchnikova. „Gradient methods for solving Stokes problem“. Ufimskii Matematicheskii Zhurnal 8, Nr. 2 (2016): 22–38. http://dx.doi.org/10.13108/2016-8-2-22.

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Vabishchevich, Petr N. „Iterative Methods for Solving Convection-diffusion Problem“. Computational Methods in Applied Mathematics 2, Nr. 4 (2002): 410–44. http://dx.doi.org/10.2478/cmam-2002-0023.

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AbstractTo obtain an approximate solution of the steady-state convectiondiffusion problem, it is necessary to solve the corresponding system of linear algebraic equations. The basic peculiarity of these LA systems is connected with the fact that they have non-symmetric matrices. We discuss the questions of approximate solution of 2D convection-diffusion problems on the basis of two- and three-level iterative methods. The general theory of iterative methods of solving grid equations is used to present the material of the paper. The basic problems of constructing grid approximations for steady-state convection-diffusion problems are considered. We start with the consideration of the Dirichlet problem for the differential equation with a convective term in the divergent, nondivergent, and skew-symmetric forms. Next, the corresponding grid problems are constructed. And, finally, iterative methods are used to solve approximately the above grid problems. Primary consideration is given to the study of the dependence of the number of iteration on the Peclet number, which is the ratio of the convective transport to the diffusive one.
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Dr. G. Geetharamani, Dr G. Geetharamani, und C. Sharmila Devi. „An Innovative Method for Solving Fuzzy Transportation Problem“. Indian Journal of Applied Research 4, Nr. 5 (01.10.2011): 399–402. http://dx.doi.org/10.15373/2249555x/may2014/124.

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Pekár, Juraj, Ivan Brezina, Jaroslav Kultan, Iryna Ushakova und Oleksandr Dorokhov. „Computer tools for solving the traveling salesman problem“. Development Management 18, Nr. 1 (30.06.2020): 25–39. http://dx.doi.org/10.21511/dm.18(1).2020.03.

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The task of the traveling salesman, which is to find the shortest or least costly circular route, is one of the most common optimization problems that need to be solved in various fields of practice. The article analyzes and demonstrates various methods for solving this problem using a specific example: heuristic (the nearest neighbor method, the most profitable neighbor method), metaheuristic (evolutionary algorithm), methods of mathematical programming. In addition to classic exact methods (which are difficult to use for large-scale tasks based on existing software) and heuristic methods, the article suggests using the innovative features of the commercially available MS Excel software using a meta-heuristic base. To find the optimal solution using exact methods, the Excel (Solver) software package was used, as well as the specialized GAMS software package. Comparison of different approaches to solving the traveling salesman problem using a practical example showed that the use of traditional heuristic approaches (the nearest neighbor method or the most profitable neighbor method) is not difficult from a computational point of view, but does not provide solutions that would be acceptable in modern conditions. The use of MS Excel for solving the problem using the methods of mathematical programming and metaheuristics enabled us to obtain an optimal solution, which led to the conclusion that modern tools are an appropriate addition to solving the traveling salesman problem while maintaining the quality of the solution.
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Yamashiro, Seiji. „Problem solving~Reconsider methods and tools for problem solving at the point of care~“. Nihon Naika Gakkai Zasshi 106, Nr. 12 (10.12.2017): 2519–22. http://dx.doi.org/10.2169/naika.106.2519.

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Au, Wing K., und John P. Leung. „Problem Solving, Instructional Methods and Logo Programming“. Journal of Educational Computing Research 7, Nr. 4 (November 1991): 455–67. http://dx.doi.org/10.2190/k88q-rwv1-avpu-3dtk.

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Dissertationen zum Thema "Methods of problem solving"

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Scanlon, Eileen. „Modelling physics problem solving“. Thesis, Open University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.277276.

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Terry, Elaine Audrey. „Problem solving methods in game theory“. DigitalCommons@Robert W. Woodruff Library, Atlanta University Center, 1988. http://digitalcommons.auctr.edu/dissertations/1796.

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Game theory is the mathematical theory associated with winning strategic and non-strategic games. In order to win a game, a player must find an optimal strategy to play. Strategies may be either pure or mixed. The latter is used when there are no pure strategies available . Games that require mixed strategies may be solved by various methods. This study is concerned with the basic theory of games. Definitions and methods for solving games are discussed. The methods for solving involve both pure and mixed strategies. The simplex method for solving linear programming problems is reviewed. The numerical examples were solved using the IBM Macintosh with the MacSimplex package.
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Santos, Trigo Luz Manuel. „College students' methods for solving mathematical problems as a result of instruction based on problem solving“. Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/31100.

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This study investigates the effects of implementing mathematical problem solving instruction in a regular calculus course taught at the college level. Principles associated with this research are: i) mathematics is developed as a response to finding solutions to mathematical problems, ii) attention to the processes involved in solving mathematical problems helps students understand and develop mathematics, and iii) mathematics is learned in an active environment which involves the use of guesses, conjectures, examples, counterexamples, and cognitive and metacognitive strategies. Classroom activities included use of nonroutine problems, small group discussions, and cognitive and metacognitive strategies during instruction. Prior to the main study, in an extensive pilot study the means for gathering data were developed, including a student questionnaire, several assignments, two written tests, student task-based interviews, an interview with the instructor, and class observations. The analysis in the study utilized ideas from Schoenfeld (1985) in which categories, such as mathematical resources, cognitive and metacognitive strategies, and belief systems, are considered useful in analyzing the students' processes for solving problems. A model proposed by Perkins and Simmons (1988) involving four frames of knowledge (content, problem solving, epistemic, and inquiry) is used to analyze students' difficulties in learning mathematics. Results show that the students recognized the importance of reflecting on the processes involved while solving mathematical problems. There are indications suggesting that the students showed a disposition to participate in discussions that involve nonroutine mathematical problems. The students' work in the assignments reflected increasing awareness of the use of problem solving strategies as the course developed. Analysis of the students' task-based interviews suggests that the students' first attempts to solve a problem involved identifying familiar terms in the problem and making some calculations often without having a clear understanding of the problem. The lack of success led the students to reexamine the statement of the problem more carefully and seek more organized approaches. The students often spent much time exploring only one strategy and experienced difficulties in using alternatives. However, hints from the interviewer (including metacognitive questions) helped the students to consider other possibilities. Although the students recognized that it was important to check the solution of a problem, they mainly focused on whether there was an error in their calculations rather than reflecting on the sense of the solution. These results lead to the conclusion that it takes time for students to conceptualize problem solving strategies and use them on their own when asked to solve mathematical problems. The instructor planned to implement various learning activities in which the content could be introduced via problem solving. These activities required the students to participate and to spend significant time working on problems. Some students were initially reluctant to spend extra time reflecting on the problems and were more interested in receiving rules that they could use in examinations. Furthermore, student expectations, evaluation policies, and curriculum rigidity limited the implementation. Therefore, it is necessary to overcome some of the students' conceptualizations of what learning mathematics entails and to propose alternatives for the evaluation of their work that are more consistent with problem solving instruction. It is recommended that problem solving instruction include the participation or coordinated involvement of all course instructors, as the selection of problems for class discussions and for assignments is a task requiring time and discussion with colleagues. Periodic discussions of course directions are necessary to make and evaluate decisions that best fit the development of the course.
Education, Faculty of
Curriculum and Pedagogy (EDCP), Department of
Graduate
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Gábor, Richard. „Project Management and Problem Solving Methods in Management Consulting“. Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-71931.

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Conducting management consulting project for Transparency International Czech Republic, the leading non-profit non-governmental organization active in anti-corruption practices, by applying selected project management and problem solving methods, the objective of the thesis is to support the assumption that proper selection and application of suitable methods to problem identification, definition and decomposition enables to come up with the solution of the problem by analyzing it with no need for further solution development.
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Hamm, Jolene Diane. „Exploring the Dimensions of Problem-solving Ability on High-achieving Secondary Students: A Mixed Methods Study“. Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/40265.

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This mixed-methods study investigated the relationship between self-concept and problem-solving style and how these two constructs compared and contrasted in regards to a participantâ s perception of his or her problem-solving ability. The 86 study participants were high-achieving rising 11th and 12th grade students attending a summer enrichment program for agriculture. This study used a concurrent triangulation mixed methods design. The quantitative aspect of the study employed two instruments, SDQ III to test perceived self-concept and the VIEW to determine the perceived problem-solving style. Concurrent with this data collection, 13 open-ended interviews were conducted to explored the description of the problem-solving process during a problem-solving event. The reason for collection of both quantitative and qualitative data was to bring together the strengths of both forms of research in order to merge the data to make comparisons and further the understanding of problem-solving ability of high-achieving youth. The study discovered that self-concept and problem-solving style have a weak relationship for many of the constructs and a negative relationship between two of constructs. The qualitative component revealed that high-achieving youth had clear definitions of problem-solving, a rich and descriptive heuristic approach, a clear understanding of which resources provided key information, and a strong depiction of themselves as problem-solver. An emergent concept from the research was the participantsâ perceptions of the team-based structure and how the inclusion of multiple ability levels versus high ability levels affected the participantsâ perceptions of solving a problem in a team situation. The mixing component of the study depicted the influence of self-concept on the problem-solving style. This study was an initial exploration of the relationship between self-concept and problem-solving and compared the current results with previous research. It extended and connected the previous research areas of self-concept and problem-solving style. As an initial study, it led to recommendations for further research across education as well as additional exploration of the emergent relationships identified. Finally, the study denoted the importance of mixed-methods research due to the interconnectivity between self-concept and problem-solving style and the participant descriptions of themselves as problem-solvers.
Ph. D.
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Ali, Ali Hasan. „Modifying Some Iterative Methods for Solving Quadratic Eigenvalue Problems“. Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1515029541712239.

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James, Alan John. „Solving the many electron problem with quantum Monte-Carlo methods“. Thesis, Imperial College London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309224.

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Rajpathak, Dnyanesh. „A generic library of problem solving methods for scheduling applications“. Thesis, Open University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417488.

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Hilal, Mohammed Azeez. „Domain decomposition like methods for solving an electrocardiography inverse problem“. Thesis, Nantes, 2016. http://www.theses.fr/2016NANT4060.

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L’objectif de cette thèse est d’étudier un problème électrocardiographique (ECG), modélisant l’activité électrique cardiaque en utilisant un modèle bidomaine stationnaire. Deux types de modélisation sont considérées : la modélisation basée sur un modèle mathématique directe et la modélisation basée sur un problème inverse de Cauchy. Dans le premier cas, le problème directe est résolu en utilisant la méthode de décomposition de domaine et l’approximation par la méthode des éléments finis. Dans le deuxième cas le problème inverse de Cauchy de l’ECG a été reformulé en un problème de point fixe. Puis, un résultat d’existence et l’unicité du point fixe basé sur les degrés topologique de Leray-Schauder a été démontré. Ensuite, quelques algorithmes itératifs régularisant et stables basés sur les techniques de décomposition de domaine ont été développés. Enfin, l’efficacité et la précision des résultats obtenus a été discutés
The aim of the this thesis is to study an electrocardiography (ECG) problem, modeling the cardiac electrical activity by using the stationary bidomain model. Tow types of modeling are considered :The modeling based on direct mathematical model and the modeling based on an inverse Cauchy problem. In the first case, the direct problem is solved by using domain decomposition methods and the approximation by finite elements method. For the inverse Cauchy problem of ECG, it was reformulated into a fixed point problem. In the second case, the existence and uniqueness of fixed point based on the topological degree of Leray-Schauder is showed. Then, some regularizing and stable iterative algorithms based on the techniques of domain decomposition method was developed. Finally, the efficiency and the accurate of the obtained results was discussed
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Sycara, Ekaterini P. „Resolving adversarial conflicts : an approach integrating case-based and analytical methods“. Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/32955.

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Bücher zum Thema "Methods of problem solving"

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Fensel, Dieter. Problem-Solving Methods. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44936-1.

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Soberón, Pablo. Problem-Solving Methods in Combinatorics. Basel: Springer Basel, 2013. http://dx.doi.org/10.1007/978-3-0348-0597-1.

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Statistical problem solving. Milwaukee: ASQC Quality Press, 1992.

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Mira, José, und José R. Álvarez, Hrsg. Artificial Neural Nets Problem Solving Methods. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44869-1.

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Cozzens, Margaret B. Problem solving using graphs. Arlington, Mass: COMAP (Consortium for Mathematics and Its Applications), 1987.

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Yeo, Anthony. Counselling: A problem-solving approach. Singapore: Armour Pub., 1993.

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Brightman, Harvey. Statistics for business problem solving. 2. Aufl. Cincinnati: College Division, South-Western Pub. Co, 1994.

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Lomuto, Nico. Problem solving methods with examples in Ada. Englewood Cliffs, NJ: Prentice-Hall, 1987.

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Problem solving methods with examples in Ada. Englewood Cliffs: Prentice-Hall, 1987.

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German, O. V. Problem solving: Methods, programming, and future concepts. Amsterdam: Elsevier, 1995.

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Buchteile zum Thema "Methods of problem solving"

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Roth, Wolff-Michael. „Problem Solving“. In First-Person Methods, 165–90. Rotterdam: SensePublishers, 2012. http://dx.doi.org/10.1007/978-94-6091-831-5_11.

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Thompson, Neil. „Problem-Solving Methods“. In People Problems, 31–160. London: Macmillan Education UK, 2006. http://dx.doi.org/10.1007/978-0-230-62818-2_2.

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Kuster, Jürg, Eugen Huber, Robert Lippmann, Alphons Schmid, Emil Schneider, Urs Witschi und Roger Wüst. „Problem-Solving Methods“. In Management for Professionals, 387–424. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45373-5_26.

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Schreiber, Guus, Bob Wielinga und Hans Akkermans. „Differentiating problem solving methods“. In Current Developments in Knowledge Acquisition — EKAW '92, 95–111. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55546-3_36.

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Loh, Mei Yoke, und Ngan Hoe Lee. „The Impact of Various Methods in Evaluating Metacognitive Strategies in Mathematical Problem Solving“. In Mathematical Problem Solving, 155–76. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10472-6_8.

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Swift, Louise, und Sally Piff. „Solving Problems“. In Quantitative Methods, 70–99. London: Macmillan Education UK, 2014. http://dx.doi.org/10.1007/978-1-137-33794-8_3.

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Swift, Louise, und Sally Piff. „Solving problems“. In Quantitative Methods, 87–122. London: Macmillan Education UK, 2010. http://dx.doi.org/10.1007/978-0-230-36582-7_3.

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Benjamins, Richard, und Christine Pierret-Golbreich. „Assumptions of problem-solving methods“. In Advances in Knowledge Acquisition, 1–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61273-4_1.

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Pescetti, Daniele. „Qualitative Methods in Problem Solving“. In Thinking Physics for Teaching, 387–99. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1921-8_32.

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Puppe, Frank. „Principles of Problem-Solving Methods“. In Systematic Introduction to Expert Systems, 101–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77971-8_12.

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Konferenzberichte zum Thema "Methods of problem solving"

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Backhouse, Roland. „Algorithmic Problem Solving — Three Years On“. In Teaching Formal Methods: Practice and Experience. BCS Learning & Development, 2006. http://dx.doi.org/10.14236/ewic/tfm2006.6.

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Mili, F., und Yee-Lan Wong. „Knowledge-level assessment of problem solving methods“. In Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences. IEEE, 1996. http://dx.doi.org/10.1109/hicss.1996.495402.

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Pytel, Krzysztof. „Fuzzy-Genetic Approach to Solving Clustering Problem“. In 2018 23rd International Conference on Methods & Models in Automation & Robotics (MMAR). IEEE, 2018. http://dx.doi.org/10.1109/mmar.2018.8486127.

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Rajawat, Shalini, Naveen Hemrajani, Ekta Menghani, R. B. Patel und B. P. Singh. „Solving Maximal Clique Problem through Genetic Algorithm“. In INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN SCIENCE AND TECHNOLOGY (ICM2ST-10). AIP, 2010. http://dx.doi.org/10.1063/1.3526202.

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Ryzhkov, L. M., und D. I. Stepurenko. „Methods for solving problem of aircraft attitude estimation“. In 2013 IEEE 2nd International Conference Actual Problems of Unmanned Air Vehicles Developments (APUAVD). IEEE, 2013. http://dx.doi.org/10.1109/apuavd.2013.6705314.

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Hales, Thomas C. „Some Methods of Problem Solving in Elementary Geometry“. In 22nd Annual IEEE Symposium on Logic in Computer Science (LICS 2007). IEEE, 2007. http://dx.doi.org/10.1109/lics.2007.43.

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Cepak, M., und V. Havlena. „New price coordination methods solving optimum allocation problem“. In 2006 IEEE Power India Conference. IEEE, 2006. http://dx.doi.org/10.1109/poweri.2006.1632636.

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Kureychik, Viktor, Vladimir Kureychik, Liliya Kureychik und Roman Potarusov. „Heuristics methods for solving the block packing problem“. In Information Technologies in Science, Management, Social Sphere and Medicine. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/itsmssm-16.2016.62.

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„TOWARDS PROBLEM SOLVING METHODS IN MULTI-AGENT SYSTEMS“. In 4th International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0002252603080313.

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Akimova, E., V. Misilov und A. Tretyakov. „Regularized methods for solving nonlinear inverse gravity problem“. In 15th EAGE International Conference on Geoinformatics - Theoretical and Applied Aspects. Netherlands: EAGE Publications BV, 2016. http://dx.doi.org/10.3997/2214-4609.201600458.

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Berichte der Organisationen zum Thema "Methods of problem solving"

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Fink, Eugene. Statistical Selection Among Problem-Solving Methods. Fort Belvoir, VA: Defense Technical Information Center, Januar 1997. http://dx.doi.org/10.21236/ada327284.

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Swartout, Bill, Yolanda Gil und Andre Valente. Representing Capabilities of Problem Solving Methods. Fort Belvoir, VA: Defense Technical Information Center, Januar 1999. http://dx.doi.org/10.21236/ada462171.

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Fischer, Ute M. Methods for Analyzing Group Problem Solving Decision Making. Fort Belvoir, VA: Defense Technical Information Center, Mai 1996. http://dx.doi.org/10.21236/ada312002.

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Piotrowska, Joanna Monika, und Jonah Maxwell Miller. Solving discontinuous problems with pseudospectral methods. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1561046.

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Gil, Yolanda. Knowledge Acquisition for Large Knowledge Bases: Integrating Problem-Solving Methods and Ontologies into Applications. Fort Belvoir, VA: Defense Technical Information Center, Juni 2001. http://dx.doi.org/10.21236/ada388168.

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Osipov, Gennadij Sergeevich. The simplest method of solving a fuzzy linear problem EXCHANGE. КультИнформПресс, 2017. http://dx.doi.org/10.18411/spbcsa-2017-4.

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Ma, Hong. Solving incompressible flow problems with parallel spectral element methods. Office of Scientific and Technical Information (OSTI), Oktober 1994. http://dx.doi.org/10.2172/183220.

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Schnabel, Robert B., und Brett William Bader. On the performance of tensor methods for solving ill-conditioned problems. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/919164.

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Peskin, Michael E. Abstract Applets: A Method for Integrating Numerical Problem Solving into the Undergraduate Physics Curriculum. Office of Scientific and Technical Information (OSTI), Februar 2003. http://dx.doi.org/10.2172/812625.

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10

Dmitriy Y. Anistratov, Adrian Constantinescu, Loren Roberts und William Wieselquist. Nonlinear Projective-Iteration Methods for Solving Transport Problems on Regular and Unstructured Grids. Office of Scientific and Technical Information (OSTI), April 2007. http://dx.doi.org/10.2172/909188.

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