Journal articles: 'Problem solving Computer simulation'

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Garrett, Michael, and Mark McMahon. "Computer-Generated Three-Dimensional Training Environments." International Journal of Gaming and Computer-Mediated Simulations 2, no. 3 (July 2010): 43–60. http://dx.doi.org/10.4018/jgcms.2010070103.

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Problem-based learning is an instructional strategy that emphasises the accumulation and development of knowledge via an active and experiential based approach to solving problems. This pedagogical framework can be instantiated using gaming technology to provide learners with the ability to control their learning experience within a dynamic, responsive, and visually rich three-dimensional virtual environment. In this regard, a conceptual framework referred to as the Simulation, User, and Problem-based Learning (SUPL) approach has been developed in order to inform the design of 3D simulation environments based on gaming technology within a problem-based learning pedagogy. The SUPL approach identifies a series of design factors relative to the user, the problem-solving task, and the 3D simulation environment that guide the learning process and facilitate the transfer of knowledge. This paper will present a simulation environment design according to this conceptual framework for a problem-solving task within the context of an underground mine emergency evacuation. The problem-solving task will be designed to satisfy learning objectives that relate to the development of knowledge and skills for emergency evacuation of the Dominion Mining’s Challenger mining operation located in South Australia.

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Axelsson, O., V. A. Barker, M. Neytcheva, and B. Polman. "SOLVING THE STOKES PROBLEM ON A MASSIVELY PARALLEL COMPUTER." Mathematical Modelling and Analysis 6, no. 1 (June 30, 2001): 7–27. http://dx.doi.org/10.3846/13926292.2001.9637141.

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We describe a numerical procedure for solving the stationary two-dimensional Stokes problem based on piecewise linear finite element approximations for both velocity and pressure, a regularization technique for stability, and a defect‐correction technique for improving accuracy. Eliminating the velocity unknowns from the algebraic system yields a symmetric positive semidefinite system for pressure which is solved by an inner‐outer iteration. The outer iterations consist of the unpreconditioned conjugate gradient method. The inner iterations, each of which corresponds to solving an elliptic boundary value problem for each velocity component, are solved by the conjugate gradient method with a preconditioning based on the algebraic multi‐level iteration (AMLI) technique. The velocity is found from the computed pressure. The method is optimal in the sense that the computational work is proportional to the number of unknowns. Further, it is designed to exploit a massively parallel computer with distributed memory architecture. Numerical experiments on a Cray T3E computer illustrate the parallel performance of the method.

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Peng, Yamian, Chunfeng Liu, and Dianxuan Gong. "Numerical Simulation Techniques Research and Application in Genetic Algorithm Design." Open Mechanical Engineering Journal 8, no. 1 (March 21, 2014): 63–68. http://dx.doi.org/10.2174/1874155x01408010063.

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Numerical simulation techniques are also called computer simulation, which take the computer as a means to study all kinds of engineering and physical problems even natural objective through numerical calculation method and image display. This paper studied the numerical simulation techniques and try to solve two-dimensional convectiondiffusion equation parameter identification inverse problem by the genetic algorithm. Firstly, the finite element method was illustrated to solve the steady problem of two-dimensional convection-diffusion equation before it compute parameter identification inverse problem each time. Subsequently, it can search the best approximate solution from many initial points and obtained the global optimum solution by means of crossover operator and mutation operator. Finally, the paper discussed the computer simulation of GA for solving the inverse problem, and puts forward a new method for solving inverse problem: Genetic algorithm based on the best disturbed iteration. The results of numerical simulation show that the genetic algorithm has the higher accuracy and the quicker convergent speed. And it is easy to program and calculate and is of great application.

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Dellarosa, Denise. "A computer simulation of children’s arithmetic word-problem solving." Behavior Research Methods, Instruments, & Computers 18, no. 2 (March 1986): 147–54. http://dx.doi.org/10.3758/bf03201014.

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Shen, Xiaojian, W. L. Scheller, and R. Kenneth Wolfe. "Solving a cafeteria dish circulation problem by computer simulation." Computers & Industrial Engineering 29, no. 1-4 (September 1995): 555–59. http://dx.doi.org/10.1016/0360-8352(95)00133-l.

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Allami, Ahmed J., Maria Grazia Concilio, Pavan Lally, and Ilya Kuprov. "Quantum mechanical MRI simulations: Solving the matrix dimension problem." Science Advances 5, no. 7 (July 2019): eaaw8962. http://dx.doi.org/10.1126/sciadv.aaw8962.

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We propose a solution to the matrix dimension problem in quantum mechanical simulations of MRI (magnetic resonance imaging) experiments on complex molecules. This problem is very old; it arises when Kronecker products of spin operators and spatial dynamics generators are taken—the resulting matrices are far too large for any current or future computer. However, spin and spatial operators individually have manageable dimensions, and we note here that the action by their Kronecker products on any vector may be computed without opening those products. This eliminates large matrices from the simulation process. MRI simulations for coupled spin systems of complex metabolites in three dimensions with diffusion, flow, chemical kinetics, and quantum mechanical treatment of spin relaxation are now possible. The methods described in this paper are implemented in versions 2.4 and later of the Spinach library.

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Mumby, Stephen J. "Solving materials problems by computer simulation." Advanced Materials 9, no. 1 (January 1997): 9–11. http://dx.doi.org/10.1002/adma.19970090102.

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Woodward, John, Douglas Carnine, and Russell Gersten. "Teaching Problem Solving Through Computer Simulations." American Educational Research Journal 25, no. 1 (January 1988): 72–86. http://dx.doi.org/10.3102/00028312025001072.

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JOHNSON, TRISTAN E., and CLARK GEDNEY. "Learning Support Assessment Study of a Computer Simulation for the Development of Microbial Identification Strategies." Microbiology Education 2, no. 1 (May 2001): 18–24. http://dx.doi.org/10.1128/me.2.1.18-24.2001.

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This paper describes a study that examined how microbiology students construct knowledge of bacterial identification while using a computer simulation. The purpose of this study was to understand how the simulation affects the cognitive processing of students during thinking, problem solving, and learning about bacterial identification and to determine how the simulation facilitates the learning of a domain-specific problem-solving strategy. As part of an upper-division microbiology course, five students participated in several simulation assignments. The data were collected using think-aloud protocol and video action logs as the students used the simulation. The analysis revealed two major themes that determined the performance of the students: Simulation Usage—how the students used the software features and Problem-Solving Strategy Development—the strategy level students started with and the skill level they achieved when they completed their use of the simulation. Several conclusions emerged from the analysis of the data: (i) The simulation affects various aspects of cognitive processing by creating an environment that makes it possible to practice the application of a problem-solving strategy. The simulation was used as an environment that allowed students to practice the cognitive skills required to solve an unknown. (ii) Identibacter (the computer simulation) may be considered to be a cognitive tool to facilitate the learning of a bacterial identification problem-solving strategy. (iii) The simulation characteristics did support student learning of a problem-solving strategy. (iv) Students demonstrated problem-solving strategy development specific to bacterial identification. (v) Participants demonstrated an improved performance from their repeated use of the simulation.

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Mandinach, Ellen B., and Marcia C. Linn. "The Cognitive Effects of Computer Learning Environments." Journal of Educational Computing Research 2, no. 4 (November 1986): 411–27. http://dx.doi.org/10.2190/tvfd-b7t8-gubf-fw86.

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The potential cognitive consequences of computers in education are just starting to emerge. The power and capabilities of computers change rapidly. Researchers often working with outmoded computer learning environments have just begun to catalog and analyze the activities that occur in these situations. There is clear agreement that computers can help students learn to solve problems and that computers might help to ameliorate the dearth of problem-solving activities in classrooms. A useful way to think about the potential advantages of the computer learning environments is in terms of a chain of cognitive accomplishments culminating in problem-solving skill. Such a chain can be identified and used to assess instruction using computers for programming, simulations, and tools such as spreadsheets. The chain emphasizes the need for students to learn templates or stereotypic sequences of actions for solving problems. It also makes clear that planning and testing are central components of problem solving. The articles in this issue illustrate how far along the chain students in typical computer learning environments progress. They offer conjectures about why students fail to proceed further and suggestions about how the situation can be improved.

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Fabianova, Jana, Jaroslava Janekova, and Jozef Horbulak. "SOLVING THE BOTTLENECK PROBLEM IN A WAREHOUSE USING SIMULATIONS." Acta logistica 8, no. 2 (June 30, 2021): 107–16. http://dx.doi.org/10.22306/al.v8i2.209.

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The uneven workload distribution and working time utilisation create a bottleneck, leading to inefficient utilisation of capacity and increased costs. A bottleneck is a limiting and risk factor for any business entity. In the case of a distribution warehouse, the bottleneck limits its ability to meet the requirements for sending an order within the required time limit. Delays at any phase of a distribution process may result in non-compliance with customer requirements. In solving capacity problems and bottlenecks elimination, computer simulations and optimisation are often used. The article presents a basic simulation analysis of workload distribution and work times, useful for logistics companies, thus for the area of human and financial resources. In the article, the use of simulations in the ExtendSim9 program to eliminate the bottleneck is discussed. The bottleneck is solved by experiments on a simulation model when optimal workers assignment to individual workplaces of the warehouse is sought. The two final proposals for workers allocation, with the current and increased number of workers, are compared in workforce utilisation and system stability. The simulation method allows verification of the proposals' impacts in advance and practically with no financial costs.

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Gorrell, Jeffrey, and Hunter Downing. "Effects of Computer-Simulated Behavior Analysis on Pre-Service Teachers' Problem Solving." Journal of Educational Computing Research 5, no. 3 (August 1989): 335–47. http://dx.doi.org/10.2190/kw8y-f816-bfvn-lqqb.

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Undergraduate students ( n = 64) enrolled in an educational psychology course were randomly assigned to groups (computer simulation, extended-instruction, problem solving, and control) to practice behavior management principles related to classroom problems. On the main dependent measure, applied problem-solving, the computer simulation group was the only group to show significantly higher level of performance on the total measure over the control group. For the targeted subskills within the applied measure, the simulation group scored significantly higher than all groups; the extended-instruction group scored significantly higher than the other two groups on the same measure. Measures of knowledge of psychological principles and of self-efficacy beliefs related to behavior management showed no differences among groups.

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Walton, Karen Doyle. "Probability, Computer Simulation, and Mathematics." Mathematics Teacher 83, no. 1 (January 1990): 22–25. http://dx.doi.org/10.5951/mt.83.1.0022.

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Many students fail to recognize the interrelationships among computers, pure mathematics, and the real world. The subject of probability can motivate students to explore various methods of problem solving, combining empirical data, simulations, and theoretical solutions. Probabilistic statements encountered in everyday life (e.g., weather predictions, state lotteries, financial forecasting) are frequently derived from the integration of observation and theoretical analysis.

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Avramiotis, Spyridon, and Georgios Tsaparlis. "Using computer simulations in chemistry problem solving." Chem. Educ. Res. Pract. 14, no. 3 (2013): 297–311. http://dx.doi.org/10.1039/c3rp20167h.

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Rivers, Robert H., and Edward Vockell. "Computer simulations to stimulate scientific problem solving." Journal of Research in Science Teaching 24, no. 5 (May 1987): 403–15. http://dx.doi.org/10.1002/tea.3660240504.

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Ennis, Catherine D., and Margaret J. Safrit. "Using a computer simulation to compare expert/novice problem-solving subroutines." British Journal of Educational Technology 22, no. 3 (September 1991): 174–86. http://dx.doi.org/10.1111/j.1467-8535.1991.tb00058.x.

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Čiegis, R., A. Dement'ev, and P. Rate. "A PARALLEL ALGORITHM FOR SOLVING ONE PROBLEM OF NONLINEAR OPTICS." Mathematical Modelling and Analysis 4, no. 1 (December 15, 1999): 58–69. http://dx.doi.org/10.3846/13926292.1999.9637111.

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This paper deals with a system of nonlinear differential equations, which describe the interaction of two focused laser beams in nonlinear media. The system of equations is approximated by a splitting finite difference scheme. A parallel version of the finite‐difference scheme is proposed and the efficiency of this algorithm is investigated. Calculations are performed using clusters of computers, connected via local computer network. The emphasis is made on solving this problem on heterogeneous clusters. In the paper a static distribution scheme is analyzed. The results of several computational experiments are presented. Data redistribution during an initial phase of computation is investigated and the influence of slow communication among the processes is taken into account during this analysis.

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JÁVOR, ANDRÁS. "SIMULATION WITH EMBEDDED AI FOR TRANSDISCIPLINARY PROBLEM SOLVING." International Journal of Modeling, Simulation, and Scientific Computing 01, no. 01 (March 2010): 85–98. http://dx.doi.org/10.1142/s179396231000002x.

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In this article, a methodology and its application in various fields is dealt with. The theoretical research work has been undertaken at the McLeod Institute of Simulation Sciences Hungarian Center and its results have been implemented in the CASSANDRA (Cognizant Adaptive Simulation System for Applications in Numerous Different Relevant Areas) simulation system. The applications covered a wide range of areas where the tool system and the methodology have been applied with success. Most of these were in the framework of international projects of the European Union.

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Yilmaz, Levent, Tuncer I. Ören, and Nasser Ghasem-Aghaee. "Simulation-based problem-solving environments for conflict studies." Simulation & Gaming 37, no. 4 (December 2006): 534–56. http://dx.doi.org/10.1177/1046878106292537.

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Müller-Merbach, H. "Heuristics: Intelligent search strategies for computer problem solving." European Journal of Operational Research 21, no. 2 (August 1985): 278–79. http://dx.doi.org/10.1016/0377-2217(85)90047-5.

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Mills, R. I. "Solving business problems by simulation." Computer-Aided Design 21, no. 8 (October 1989): 535. http://dx.doi.org/10.1016/0010-4485(89)90063-8.

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Ruiz Ledesma, Elena Fabiola, and Juan Jesús Gutiérrez García. "Simulation as a Resource in the Calculus Solving Problem." International Journal of Systems Applications, Engineering & Development 15 (November 28, 2021): 172–77. http://dx.doi.org/10.46300/91015.2021.15.25.

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This article is derived from the research project and developed at School of Computer Sciences of the National Polytechnic Institute of Mexico. The article reports on the problems found among engineering students with respect to their resistance to using different representation registers when solving optimization problems in the Calculus Learning Unit. Use of such registers could help the students to build mathematics knowledge and to solve calculus problems. As a didactic strategy, simulations are used in an electronic environment in order to support the students by fostering their use of tabular, graphical and algebraic representation registers. Interviews are undertaken of six of the professors who gave the calculus courses, and a diagnostic questionnaire was applied to 68 students prior to and after working with the proposal. As for the theoretical framework, the work reported by Duval and Hitt is salient in this report, particularly their emphasis of the fact that working on activities by way of one single representation system is not sufficient. From the first responses provided by the students, one can conclude that the algebraic register is preferred by the majority of students. It is however used in a mechanical fashion without affording any meaning to the content of the problem and to the process of solving it. Another conclusion reported is that implementing tasks in the classroom in which the mathematics activity requires coherent use of different representations is necessary

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Woodward, John P., Douglas Carnine, and Lorraine G. Davis. "Health ways: a computer simulation for problem solving in personal health management." Family & Community Health 9, no. 2 (August 1986): 60–63. http://dx.doi.org/10.1097/00003727-198608000-00008.

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Chandler, Terrell N., and Christine Chaillé. "Process Highlighters in a Computer Simulation: Facilitation of Theory-Oriented Problem Solving." Journal of Educational Computing Research 9, no. 2 (May 1993): 237–63. http://dx.doi.org/10.2190/3ggg-k9cc-19xc-9g0w.

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This experiment investigates whether or not process highlighters, incorporated in a computer simulation, facilitate the knowledge representation of early adolescent children. Process highlighters are perceptual cues (usually visual) that are designed to focus attention toward critical features of events and processes occurring in a problem domain. The two questions addressed in this study are: a) do process highlighters increase the percentage of subjects who employ theory-oriented explanation?, and b) do process highlighters increase the percentage of subjects who demonstrate an understanding of the concept presented in the simulation? Thirty-two twelve-year-old children from two middle schools played a computer game about light reflecting off flat mirrors, presenting the physical law that the angle of incidence equals the angle of reflection. Each child played either the game with process highlighters or the game without process highlighters for forty minutes. Three independent evaluators analyzed each subject's transcript to determine his/her mode of explanation (random, concrete, or hypothetical) and also the level of understanding (none, preliminary, or good). The results indicate that the use of process highlighters is positively correlated with the subject's level of understanding, but is less conclusive with respect to encouraging students to use theory-oriented problem solving. The results are interpreted with respect to clarifying the relationship between a student's understanding of a concept and his or her expressing that understanding in concrete or hypothetical terms.

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SENGUPTA, BIKRAM, ANSHU JAIN, KAMAL BHATTACHARYA, HONG-LINH TRUONG, and SCHAHRAM DUSTDAR. "COLLECTIVE PROBLEM SOLVING USING SOCIAL COMPUTE UNITS." International Journal of Cooperative Information Systems 22, no. 04 (December 2013): 1341002. http://dx.doi.org/10.1142/s0218843013410025.

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Service process orchestration using workflow technologies has led to significant improvements in generating predicable outcomes by automating tedious manual tasks but suffer from challenges related to the flexibility required in work especially when humans are involved. Recently emerging trends in enterprises to explore social computing concepts have realized value in more agile work process orchestrations but tend to be less predictable with respect to outcomes. In this paper, we use IT services management, specifically, incident management for large scale systems, to investigate the interplay of workflow systems and social computing. We apply a recently introduced concept of social compute units (SCU), and flexible teams sourced based on various parameters such as skills, availability, incident urgency, etc. in the context of resolution of incidents in an IT service provider organization. Results from simulation-based experiments indicate that the combination of SCUs and workflow based processes can lead to significant improvement in key service delivery outcomes, with average resolution time per incident and number of SLO violations being at times as low as 53.7% and 38.1%, respectively of the corresponding values for pure workflow based incident management. Moreover, significant benefits may also be obtained through cross-skilling of practitioners via exposure to new skills in the context of collaborative work.

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Farahmand, Kambiz, Satpal Singh Wadhwa, and Mahmoud Mostafa. "INTEGRATING ANIMATION INTO TEACHING COMPUTER SIMULATION." INTERNATIONAL JOURNAL OF RESEARCH IN EDUCATION METHODOLOGY 7, no. 3 (August 30, 2016): 1176–81. http://dx.doi.org/10.24297/ijrem.v7i3.3827.

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Computer simulation is an experiment using a computer model to represent a unique system.Â Variables are defined and parameters to be study are monitored and recorded. Growing caÂpabilities and decreasing costs of microcomputers are placing this powerful tool at the fingertips of scientists and engineers. In the past, the use of digital computers in simulation required a considerable amount of programming effort. This is no longer a true statement.Â Simulation provides the student with a greater breadth and depth of information on which decisions could be made. It is also considered one of the most valuable and flexible decision making tools available. Flexible simulation and animation models developed using a multitude of softwareâ€™s available in the market today is considered a very powerful and effective approach in engineering education. Simulation and animation models could easily be used to solve complex and dynamic problems in both the classroom and real life.Computer simulation techniques and soft wares have been used for more than a decade to help engineers in development, trouble shooting, problem solving, and decision making process. The new paradigm in computer simulation is the use of animation and virtual reality to build engineering models and animation, simulate operations and performance. The fantastic progress in computer hardware and software industry has now opened a new and higher level of teaching computer simulation.

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Hollingsworth, Maurice, and John Woodward. "Integrated Learning: Explicit Strategies and Their Role in Problem-Solving Instruction for Students with Learning Disabilities." Exceptional Children 59, no. 5 (March 1993): 444–55. http://dx.doi.org/10.1177/001440299305900507.

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This study investigated the effectiveness of an explicit strategy as a means of linking facts, concepts, and problem solving in an unfamiliar domain of learning. Participants were 37 secondary students with learning disabilities. All students were taught health facts and concepts, which they then applied to problem-solving exercises presented through computer-simulation games. Students in the experimental group were taught an explicit strategy for solving the problems; the comparison group was given supportive feedback and encouraged to induce their own strategies. The explicit strategy group performed significantly better on two transfer measures, including videotaped problem-solving exercises.

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Hsu, Jerry, Nghia Truong, Cem Yuksel, and Kui Wu. "A general two-stage initialization for sag-free deformable simulations." ACM Transactions on Graphics 41, no. 4 (July 2022): 1–13. http://dx.doi.org/10.1145/3528223.3530165.

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Initializing simulations of deformable objects involves setting the rest state of all internal forces at the rest shape of the object. However, often times the rest shape is not explicitly provided. In its absence, it is common to initialize by treating the given initial shape as the rest shape. This leads to sagging, the undesirable deformation under gravity as soon as the simulation begins. Prior solutions to sagging are limited to specific simulation systems and material models, most of them cannot handle frictional contact, and they require solving expensive global nonlinear optimization problems. We introduce a novel solution to the sagging problem that can be applied to a variety of simulation systems and materials. The key feature of our approach is that we avoid solving a global nonlinear optimization problem by performing the initialization in two stages. First, we use a global linear optimization for static equilibrium. Any nonlinearity of the material definition is handled in the local stage, which solves many small local problems efficiently and in parallel. Notably, our method can properly handle frictional contact orders of magnitude faster than prior work. We show that our approach can be applied to various simulation systems by presenting examples with mass-spring systems, cloth simulations, the finite element method, the material point method, and position-based dynamics.

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Wu, Dongqing, and Yunong Zhang. "From Penrose Equations to Zhang Neural Network, Getz–Marsden Dynamic System, and DDD (Direct Derivative Dynamics) Using Substitution Technique." Discrete Dynamics in Nature and Society 2021 (November 20, 2021): 1–21. http://dx.doi.org/10.1155/2021/4227512.

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The time-variant matrix inversion (TVMI) problem solving is the hotspot of current research because of its frequent appearance and application in scientific research and industrial production. The generalized inverse problem of singular square matrix and nonsquare matrix can be related to Penrose equations (PEs). The PEs implicitly define the generalized inverse of a known matrix, which is of fundamental theoretical significance. Therefore, the in-depth study of PEs might enlighten problem solving of TVMI in a foreseeable way. For the first time, we construct three different matrix error-monitoring functions based on PEs and propose the corresponding models for TVMI problem solving by using the substitution technique and ZNN design formula. In order to facilitate computer simulation, the obtained continuous-time models are discretized by using ZTD (Zhang time discretization) formulas. Furthermore, the feasibility and effectiveness of the novel Zhang neural network (ZNN) multiple-multiplication model for matrix inverse (ZMMMI) and the PEs-based Getz–Marsden dynamic system (PGMDS) model in solving the problem of TVMI are investigated and shown via theoretical derivation and computer simulation. Computer experiment results also illustrate that the direct derivative dynamics model for TVMI is less effective and feasible.

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Chance, Joseph E., and Pearl W. Brazier. "Two Problems That Illustrate the Techniques of Computer Simulation." Mathematics Teacher 79, no. 9 (December 1986): 726–31. http://dx.doi.org/10.5951/mt.79.9.0726.

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Most introductory courses in computing include a discussion or illustration of the technique of simulation (Gear 1978, 55-59; Pohl and Shaw 1981. 235-362). Problems involving simulation illustrate the enormous computational abilities of even a microcomputer and, more important, allow the student to observe a new facet of mathematical thinking. A traditional mathematics curriculum prepares the student to use deductive reasoning in problem solving, with little stress on inductive methods of solution. The reason generally given for such neglect is that it is impossible to consider an “adequate number” of cases for an inductive solution. Such reasoning must be reevaluated when one considers the possibilities available to the computer user.

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Hwang, M. J., C. I. Chiang, and Y. H. Liu. "Solving a fuzzy set-covering problem." Mathematical and Computer Modelling 40, no. 7-8 (October 2004): 861–65. http://dx.doi.org/10.1016/j.mcm.2004.10.015.

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Fletcher, Charles R. "Understanding and solving arithmetic word problems: A computer simulation." Behavior Research Methods, Instruments, & Computers 17, no. 5 (September 1985): 565–71. http://dx.doi.org/10.3758/bf03207654.

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Mandinach, Ellen B. "Model-Building and the Use of Computer Simulation of Dynamic Systems." Journal of Educational Computing Research 5, no. 2 (May 1989): 221–43. http://dx.doi.org/10.2190/7w4f-xy0h-l6fh-39r8.

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The Systems Thinking and Curriculum Innovation (STACI) Project is a multi-year research effort intended to examine the cognitive impact of learning from a systems thinking approach to instruction and from using simulation-modeling software. Systems thinking is an analytic problem solving tool that can be integrated into courses to supplement and enhance instruction in a variety of content areas. The purpose of the study is to test the potentials and effects of using the technology-based approach in secondary school curricula to teach content-specific knowledge as well as general problem solving skills. The research focuses on the effects of introducing a software environment that enables students to learn from and make concrete multiple representations of scientific, mathematical, and historical phenomena.

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Coulter, Xenia. "A New Way of Teaching Statistics." Journal of Educational Technology Systems 24, no. 2 (December 1995): 181–87. http://dx.doi.org/10.2190/k906-0m2x-cgte-7xgv.

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Teaching statistics through computer-assisted simulations eliminates the constraints and challenges associated with teaching the course using mathematics. It also provides students with a practical means for solving real-life problems and a solid conceptual grasp of the problem-solving nature of the discipline. A text that deemphasizes mathematics and introduces simulation as a means of understanding concepts, along with software designed for computer-intensive statistical methods and a workbook of journal article selections provide the foundation materials for such a study of statistics. A special course guide also was developed to provide a clear introduction to the software for naive users, show how the software and the text are related, and connect the simulation techniques to standard statistical tests. Altogether these materials not only provide a positive experience for students studying statistics, but they allow them to study the subject independently and at a distance.

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Simmons, Patricia E., and Vincent N. Lunetta. "Problem-solving behaviors during a genetics computer simulation: Beyond the expert/novice dichotomy." Journal of Research in Science Teaching 30, no. 2 (February 1993): 153–73. http://dx.doi.org/10.1002/tea.3660300204.

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Xu, Haochen, Guanhua Fang, Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. "Latent Class Analysis of Recurrent Events in Problem-Solving Items." Applied Psychological Measurement 42, no. 6 (April 9, 2018): 478–98. http://dx.doi.org/10.1177/0146621617748325.

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Computer-based assessment of complex problem-solving abilities is becoming more and more popular. In such an assessment, the entire problem-solving process of an examinee is recorded, providing detailed information about the individual, such as behavioral patterns, speed, and learning trajectory. The problem-solving processes are recorded in a computer log file which is a time-stamped documentation of events related to task completion. As opposed to cross-sectional response data from traditional tests, process data in log files are massive and irregularly structured, calling for effective exploratory data analysis methods. Motivated by a specific complex problem-solving item “Climate Control” in the 2012 Programme for International Student Assessment, the authors propose a latent class analysis approach to analyzing the events occurred in the problem-solving processes. The exploratory latent class analysis yields meaningful latent classes. Simulation studies are conducted to evaluate the proposed approach.

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Semerikov, Serhiy, Illia Teplytskyi, Yuliia Yechkalo, Oksana Markova, Vladimir Soloviev, and Arnold Kiv. "Using spreadsheets as learning tools for computer simulation of neural networks." SHS Web of Conferences 75 (2020): 04018. http://dx.doi.org/10.1051/shsconf/20207504018.

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The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment with-out add-ins and macros. The article considers ways of building neural network models in cloud-based spreadsheets, Google Sheets. The model is based on the problem of classifying multi-dimensional data provided in “The Use of Multiple Measurements in Taxonomic Problems” by R. A. Fisher. Edgar Anderson’s role in collecting and preparing the data in the 1920s-1930s is discussed as well as some peculiarities of data selection. There are presented data on the method of multi-dimensional data presentation in the form of an ideograph developed by Anderson and considered one of the first efficient ways of data visualization.

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Khoroshev, Artem. "Simulation of Nonlinear Magnetic Systems by the Finite Element Method Using BLR-Factorization." Известия высших учебных заведений. Электромеханика 64, no. 4-5 (2021): 14–19. http://dx.doi.org/10.17213/0136-3360-2021-4-5-14-19.

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The possibility of practical application of BLR-factorization (low-rank approximation of the matrix of un-knowns of a system of linear equations) for finite element modeling of the electromagnetic field topology of nonlinear magnetic systems is considered. A method for estimating the accuracy of the computed solution of the SLAE and the nature of the influence of the given accuracy of the low-rank approximation of the matrix of un-knowns on the upper limit of the relative forward error of the computed solution of the SLAE are shown. Using a model problem as an example, the dependence of the accuracy of calculating the integral characteristics of an electromechanical apparatus on the tolerance of the low-rank approximation of the matrix of unknowns is shown, as well as its effect on the convergence of the process of solving a nonlinear numerical problem. A quantitative assessment of the reduction in the computational complexity of the process of solving a numerical problem and the required amount of computer memory for solving the SLAE is carried out. The applicability of BLR-factorization for finite element modeling of the topology of the electromagnetic field without the use of numerical methods of the Krylov subspace is estimated.

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Bai, Li Xia, Shun Chu Li, Dong Dong Gui, Cong Yin Fan, Xiao Xu Dong, and Bin Zhou. "Similar Structure Algorithm for Solving Boundary Value Problem of Differential Equations." Applied Mechanics and Materials 574 (July 2014): 665–71. http://dx.doi.org/10.4028/www.scientific.net/amm.574.665.

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Based on the similar structure theory, we conduct rigorous mathematical derivation and proof for the boundary value problem of a class of differential equation . We put forward a new algorithm------Similar Structure Algorithm to solve such boundary value problems. The similar structure algorithm only includes arithmetic and logical operation, hence it can be oriented towards computer. According to the similar structure algorithm, an example is given to conduct a simulation experiment by the application of computer software at the end of the paper. And we also observe and analysis the variational laws of the laboratory result by changing the coefficient of the boundary condition.

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Jiang, H. "Solving Multi-Robot Picking Problem in Warehouses: a Simulation Approach." International Journal of Simulation Modelling 19, no. 4 (December 5, 2020): 701–12. http://dx.doi.org/10.2507/ijsimm19-4-co19.

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This paper focuses on the order batching problem, aiming at this order batching problem of an e-commerce unmanned warehouse multi-robot picking system, considering the complexity and uncertainty of the system. In this paper establishes a two-stage model with the objective function of maximizing the sum of the average similarity of each picking station and balancing the picking station picking times, and uses a dynamic clustering algorithm to solve the model. The simulation results show that a two-stage order batching model that considers the order similarity and the picking time balance can be established, which can reduce the number of shelves effectively and improve the picking efficiency of warehouse multi-robot system.

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Andrade, Leo Pasqualini de, Augusto Cláudio Santa Brígida Tirado, Valério Brusamolin, and Mateus Das Neves Gomes. "Solving a hypothetical chess problem: a comparative analysis of computational methods and human reasoning." Revista Brasileira de Computação Aplicada 11, no. 1 (April 15, 2019): 96–103. http://dx.doi.org/10.5335/rbca.v11i1.9111.

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Computational modeling has enabled researchers to simulate tasks which are very often impossible in practice, such as deciphering the working of the human mind, and chess is used by many cognitive scientists as an investigative tool in studies on intelligence, behavioral patterns and cognitive development and rehabilitation. Computer analysis of databases with millions of chess games allows players’ cognitive development to be predicted and their behavioral patterns to be investigated. However, computers are not yet able to solve chess problems in which human intelligence analyzes and evaluates abstractly without the need for many concrete calculations. The aim of this article is to describe and simulate a chess problem situation proposed by the British mathematician Sir Roger Penrose and thus provide an opportunity for a comparative discussion by society of human and artificial intelligence. To this end, a specialist chess computer program, Fritz 12, was used to simulate possible moves for the proposed problem. The program calculated the variations and reached a different result from that an amateur chess player would reach after analyzing the problem for only a short time. New simulation paradigms are needed to understand how abstract human thinking works.

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Liu, Lu. "Solving 0-1 Knapsack Problems by Greedy Method and Dynamic Programming Method." Advanced Materials Research 282-283 (July 2011): 570–73. http://dx.doi.org/10.4028/www.scientific.net/amr.282-283.570.

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The 0-1 knapsack problem is typical problem in computer science and its solution is a hot spot in algorithms design and verification. Because it is very hard to solve, it is very important in the research on cryptosystem and number theory. In this paper, the 0-1 knapsack problem and its algorithm is analyzed firstly. And then this paper presents two kinds of expand form, and proposes two efficient algorithms based on dynamic programming and greedy algorithm to solve the proposed problems. Simulation results show it is effective.

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Shih, Hsu-Shih, Chih-Hung Wang, and E. S. Lee. "A multiattribute GDSS for aiding problem-solving." Mathematical and Computer Modelling 39, no. 11-12 (June 2004): 1397–412. http://dx.doi.org/10.1016/j.mcm.2004.06.014.

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Rodríguez, Alejandro, and James A. Reggia. "Extending Self-Organizing Particle Systems to Problem Solving." Artificial Life 10, no. 4 (September 2004): 379–95. http://dx.doi.org/10.1162/1064546041766424.

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Self-organizing particle systems consist of numerous autonomous, purely reflexive agents (“particles”) whose collective movements through space are determined primarily by local influences they exert upon one another. Inspired by biological phenomena (bird flocking, fish schooling, etc.), particle systems have been used not only for biological modeling, but also increasingly for applications requiring the simulation of collective movements such as computer-generated animation. In this research, we take some first steps in extending particle systems so that they not only move collectively, but also solve simple problems. This is done by giving the individual particles (agents) a rudimentary intelligence in the form of a very limited memory and a top-down, goal-directed control mechanism that, triggered by appropriate conditions, switches them between different behavioral states and thus different movement dynamics. Such enhanced particle systems are shown to be able to function effectively in performing simulated search-and-collect tasks. Further, computational experiments show that collectively moving agent teams are more effective than similar but independently moving ones in carrying out such tasks, and that agent teams of either type that split off members of the collective to protect previously acquired resources are most effective. This work shows that the reflexive agents of contemporary particle systems can readily be extended to support goal-directed problem solving while retaining their collective movement behaviors. These results may prove useful not only for future modeling of animal behavior, but also in computer animation, coordinated movement control in robotic teams, particle swarm optimization, and computer games.

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Simanjuntak, Mariati Purnama, Juniar Hutahaean, Nurliana Marpaung, and Dewi Ramadhani. "Effectiveness of Problem-Based Learning Combined with Computer Simulation on Students’ Problem-Solving and Creative Thinking Skills." International Journal of Instruction 14, no. 3 (July 1, 2021): 519–34. http://dx.doi.org/10.29333/iji.2021.14330a.

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SADAOUI, SAMIRA, MALEK MOUHOUB, and BO CHEN. "AN EFFICIENT LOTOS-BASED FRAMEWORK FOR DESCRIBING AND SOLVING (TEMPORAL) CSPs." International Journal of Software Engineering and Knowledge Engineering 19, no. 06 (September 2009): 765–89. http://dx.doi.org/10.1142/s0218194009004416.

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Simulation of complex Lotos specifications is not always efficient due to the space explosion problem of their corresponding transition systems. To overcome this difficulty in practice, we present in this paper a novel approach which integrates constraint propagation techniques into the Lotos specifications. These solving techniques are used to reduce the size of the search space before and during the search for a solution to a given combinatorial problem under constraints. In order to do that, we first tackle the challenging task of describing combinatorial problems in Lotos using the Constraint Satisfaction Problem (CSP) framework. In this regard, we provide two generic Lotos templates for describing CSPs and temporal CSPs (CSPs involving temporal constraints). To evaluate the time performance of the framework we propose, we have conducted several experimental tests on instances of the N-Queens, the machine scheduling and randomly generated CSPs. The results of these experiments are promising and demonstrate the efficiency of Lotos simulation when CSP techniques are integrated.

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Tang, Xiu Ying, Jie Shi, Li Chang Chen, Lin Lin Yang, and Xue Mei Leng. "Logistics Simulation and Optimization Design of One Production Line Based on Flexsim." Applied Mechanics and Materials 397-400 (September 2013): 2622–25. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2622.

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At present, with the rapid development of manufacturing industry, the problem in the production process is constantly exposed. This kind of production system is very complicated that it is often the spatial variable, time variable and random variable interdependent dynamic problems. The computer simulation software is the one of the best effective way to find out the problems existing in the production process. This paper takes one product line as example, using Flexsim simulation software in the production line for modeling and simulation. Then the simulation test and simulation analysis is done to find out the bottleneck of the system. Finally proposal is given to solving the bottleneck problem, and Flexsim simulation of new distribution is proved that it could improve the efficiency of the production line.

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Newell, Markeda. "Exploring the Use of Computer Simulation to Evaluate the Implementation of Problem-Solving Consultation." Journal of Educational and Psychological Consultation 20, no. 3 (September 7, 2010): 228–55. http://dx.doi.org/10.1080/10474412.2010.500511.

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Rooeinfar, R., S. Raissi, and VR Ghezavati. "Stochastic flexible flow shop scheduling problem with limited buffers and fixed interval preventive maintenance: a hybrid approach of simulation and metaheuristic algorithms." SIMULATION 95, no. 6 (November 15, 2018): 509–28. http://dx.doi.org/10.1177/0037549718809542.

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This study focused on the uncertain flexible flow shop scheduling problem with limited buffers when preventive maintenance is applied at fixed intervals. This issue has not been addressed in spite of widespread applications, due to complexity arising in solving such a stochastic decision making problem. To this aim, a novel optimization model is presented along with two types of solving methods using metaheuristic algorithms with and without a computer simulation model. The proposed hybrid method, named HSIM-META, integrates the computer simulation model along with the three most common metaheuristic algorithms, i.e., genetic algorithm (GA), simulated annealing (SA) algorithm, and particle swarm optimization (PSO), which offer better solution quality according to the literature. For this purpose, the simulation outputs are applied as an initial population for the tuned metaheuristic parameters to look for the next improved solution by investigating different approaches. Different numerical examples are discussed to examine the performance of the proposed method. The computational results of the proposed method, including hybrid simulation with GA (HSIM-GA), SA (HSIM-SA), and PSO (HSIM-PSO), are compared with the just applying GA, SA, and PSO. The results reveal that the suggested method acts more efficiently in terms of accuracy and speed in solving the problem.

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Kornilov, Viktor S. "Development of students’ scientific knowledge on computer modeling while teaching inverse problems for differential equations." RUDN Journal of Informatization in Education 19, no. 1 (March 29, 2022): 54–61. http://dx.doi.org/10.22363/2312-8631-2022-19-1-54-61.

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Problem statement. Currently, the higher school provides students of physical and mathematical training areas with fundamental subject knowledge, forms professional competencies, develops creative abilities and creativity, teaches them to use modern computer technologies to solve applied problems. One of such academic disciplines, in which students are taught to use computer technologies in solving applied mathematical problems, is a training course called Inverse problems for differential equations. Such an academic discipline has been taught in some Russian universities in the form of elective courses since the 70s of the 20th century. The educational material of this training course includes advanced research results on inverse problems belonging to specialists from different countries, such as Germany, Italy, China, Sweden, Netherlands, Russia, Japan and other foreign countries. During the practical classes, much attention is paid to the use of computer simulation for the study of such applied problems. This circumstance implies the development of educational materials taking into account the professional training of university students, in which attention should be paid to the use of computer modeling in solving mathematical models of inverse problems. Methodology. The implementation of training of university students in physical and mathematical areas of training involves taking into account modern scientific achievements of world science in the field of inverse problems using computer simulation and implementing advanced pedagogical technologies in the classroom. Results. Students acquire scientific knowledge of computer modeling and master the wide possibilities of computer modeling in the study of inverse problems. Conclusion. The presence of scientific knowledge in the field of computer simulation and practical experience of its application for solving inverse problems gives students great advantages and opportunities to be successful specialists in the field of applied mathematics and to be in demand on the labor market in various spheres of human activity.

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Journal articles on the topic 'Problem solving Computer simulation'

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