Journal articles: 'Risk management Computer simulation'

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Bučková, Monika, Miroslav Fusko, Gabriela Gabajová, Martin Gašo, Branislav Mičieta, and Milan Martinkovič. "MANAGING RISK WITH THE USE OF COMPUTER SIMULATION." Proceedings of CBU in Economics and Business 2 (October 24, 2021): 17–23. http://dx.doi.org/10.12955/peb.v2.250.

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Internal and external risk management has become an important issue in today's global business environment, which is fraught with health, natural, political, economic and technical threats. This article deals with the design of a methodology for problem-solving and risk management in connection with computer simulation. The risk management methodology proposed by us consists of individual steps, which are summarized into three stages - risk assessment, risk analysis and risk management. The proposed computer simulation methodology consists of several steps, for example creating a parametric simulation model, designing experiments, analysis of the simulation model results or the evaluation of the simulation results. These steps are described in the article. After completing the previous steps, we describe the points of an action plan and what it must contain to avoid consequences and the impact of risks at the lowest possible level. An example of the use of computer simulation is the risk situation associated with the fluctuation of employees. In the end, the proposed methodology is supported by the results of our research and its further direction.

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BETTER, MARCO, FRED GLOVER, GARY KOCHENBERGER, and HAIBO WANG. "SIMULATION OPTIMIZATION: APPLICATIONS IN RISK MANAGEMENT." International Journal of Information Technology & Decision Making 07, no. 04 (December 2008): 571–87. http://dx.doi.org/10.1142/s0219622008003137.

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Simulation optimization is providing solutions to important practical problems previously beyond reach. This paper explores how new approaches are significantly expanding the power of simulation optimization for managing risk. Recent advances in simulation optimization technology are leading to new opportunities to solve problems more effectively. Specifically, in applications involving risk and uncertainty, simulation optimization surpasses the capabilities of other optimization methods not only in the quality of solutions but also in their interpretability and practicality. In this paper, we demonstrate the advantages of using a simulation optimization approach to tackle risky decisions, by showcasing the methodology on two popular applications from the areas of finance and business process design.

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Ashton, David, Gregory B. Getts, Peter H. Ritchken, and Harvey M. Salkin. "Portfolio Risk Management: A Computer Simulation for Stocks and Options." Economic Journal 100, no. 401 (June 1990): 655. http://dx.doi.org/10.2307/2234170.

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Thornton, A. C. "Variation Risk Management Using Modeling and Simulation." Journal of Mechanical Design 121, no. 2 (June 1, 1999): 297–304. http://dx.doi.org/10.1115/1.2829457.

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Design and manufacturing firms are under significant pressure to simultaneously increase product complexity, reduce design cycles, decrease cost, and improve quality. A key enabler to reduce cost without sacrificing quality is the control of variation during both design and manufacturing. The best time to reduce the impact of variation is in the early stages of design. This paper presents a tool set used to identify, early in the design process, where variation will have significant impact on the final cost and quality of a product. It presents the design team with a graphical view of variation risk, enabling them to quickly identify high-risk areas. The uncertainty about process capability and risk is also quantified and presented to the user.

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Landström, Catharina, and Sarah J. Whatmore. "Virtually Expert: Modes of Environmental Computer Simulation Modeling." Science in Context 27, no. 4 (November 13, 2014): 579–603. http://dx.doi.org/10.1017/s0269889714000210.

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ArgumentThis paper challenges three assumptions common in the literature on expertise: that expertise is linearly derived from scientific knowledge; that experts always align with the established institutional order; and that expertise is a property acquired by individuals. We criticize these ideas by juxtaposing three distinct expert practices involved with flood risk management in England. Virtual engineering is associated with commercial consultancy and relies on standardized software packages to assess local flood inundation. Mathematical experimentation refers to academic scientists creating new digital renderings of the physical dynamics of flooding. Participatory modeling denotes research projects that aim to transform the relationships between experts and local communities. Focusing on different modes of modeling we contribute an analysis of how particular models articulate with specific politics of knowledge as experts form relationships with flood risk management actors. Our empirical study also shows how models can contribute to re-distribution of expertise in local flood risk management.

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Kok, Bethany E., Declan Dagger, Conor Gaffney, and Austin Kenny. "Experiential Learning at Scale with Computer-Based Roleplay Simulations." International Journal of Advanced Corporate Learning (iJAC) 11, no. 2 (December 19, 2018): 24. http://dx.doi.org/10.3991/ijac.v11i2.9364.

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Experiential learning is an effective method for changing behavior and teaching new material at work. Unfortunately, experiential learning is difficult to deliver at scale as it requires hands-on participation and interactivity.EmpowerTheUser (ETU)’s computer-based roleplay simulations enable experiential learning at scale. In a simulation, learners take on a role and have to react to various situations and make choices that have downsteam consequences. ETU Simulations engage the learner in cycles of assessment and practice, with summative scoring in the assessment mode and real time coaching and feedback in the practice mode. ETU partnered with one of the oldest custodian banks headquartered in New York to deliver a series of three simulations on risk management to nearly 6,000 managers on five continents. User feedback shows that learners are highly satisfied with the program. Performance improved from simulation I to simulation II, indicating transfer of learning. Underperforming learners were remediated using the assess/practice/assess learning loop, resulting in a 227% improvement in performance.EmpowerTheUser Simulations provided fast, consistent training in risk management. Feedback was overwhelmingly favorable and decision tracking within the simulations demonstrated effective learning.

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Lamé, Guillaume, and Rebecca K. Simmons. "From behavioural simulation to computer models: how simulation can be used to improve healthcare management and policy." BMJ Simulation and Technology Enhanced Learning 6, no. 2 (October 20, 2018): 95–102. http://dx.doi.org/10.1136/bmjstel-2018-000377.

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Simulation is a technique that evokes or replicates substantial aspects of the real world, in order to experiment with a simplified imitation of an operations system, for the purpose of better understanding and/or improving that system. Simulation provides a safe environment for investigating individual and organisational behaviour and a risk-free testbed for new policies and procedures. Therefore, it can complement or replace direct field observations and trial-and-error approaches, which can be time consuming, costly and difficult to carry out. However, simulation has low adoption as a research and improvement tool in healthcare management and policy-making. The literature on simulation in these fields is dispersed across different disciplinary traditions and typically focuses on a single simulation method. In this article, we examine how simulation can be used to investigate, understand and improve management and policy-making in healthcare organisations. We develop the rationale for using simulation and provide an integrative overview of existing approaches, using examples of in vivo behavioural simulations involving live participants, pure in silico computer simulations and intermediate approaches (virtual simulation) where human participants interact with computer simulations of health organisations. We also discuss the combination of these approaches to organisational simulation and the evaluation of simulation-based interventions.

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Frolova, Nina, Valery Larionov, Jean Bonnin, Sergey Suchshev, Alexander Ugarov, and Nataliya Malaeva. "Impact database application for natural and technological risk management." Natural Hazards and Earth System Sciences 20, no. 1 (January 13, 2020): 95–106. http://dx.doi.org/10.5194/nhess-20-95-2020.

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Abstract. Impact database development and application for risk analysis and management promote the usage of self-learning computer systems with elements of artificial intelligence. Such system learning could be successful when the databases store the complete information about each event, parameters of the simulation models, the range of its application, and residual errors. Each new description included in the database could increase the reliability of the results obtained with application of simulation models. The calibration of mathematical models is the first step to self-learning of automated systems. The article describes the events' database structure and examples of calibrated computer models as applied to the impact of expected emergencies and risk indicator assessment. Examples of database statistics usage in order to rank the subjects of the Russian Federation by the frequency of emergencies of different character as well as risk indicators are given.

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Landström, Catharina, Sarah J. Whatmore, and Stuart N. Lane. "Virtual Engineering." Science & Technology Studies 24, no. 2 (January 1, 2011): 3–22. http://dx.doi.org/10.23987/sts.55261.

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This paper discusses computer simulation modelling in the context of environmental risk management. Approaching computer simulation as practice, performed in networks of heterogeneous elements, we examine the modelling undertaken by engineering consultants commissioned to provide knowledge about local flood risk to the Environment Agency of England and Wales (EA), the public body responsible for flood risk management. We propose that this simulation modelling is best understood as a form of engineering, work geared to solving the problems of clients. It is also a ‘virtual’ activity, articulating risks and possibilities in the digital space of the computer. We find that this ‘virtual engineering’ is shaped by the demands and protocols of the EA, first, by the establishment of long-term contractual agreements for delivering knowledge and second, by an EA requirement to use particular software packages. Fashioned between long-term contracts and black-boxed software virtual engineering becomes stabilised as ‘the’ way in which knowledge about flood risk in actual localities is generated and, consequently, becomes ‘hard-wired’ into flood risk management in England.

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Shao, Xin Peng, Hui Ji, Shu Ming Yan, Qi Qian Li, Ning Jia, Min Jing, Liang Ma, Kun Jing, Ya Ping Liang, and Hai Xia Yu. "Correlation Analysis of Computer Simulation with Full-Scale Impact Test for Barrier Safety Evaluation." Applied Mechanics and Materials 94-96 (September 2011): 2092–101. http://dx.doi.org/10.4028/www.scientific.net/amm.94-96.2092.

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In order to analyze the feasibility of barrier safety performance evaluation with computer simulation method, finite-element models of various vehicles and barriers were set up and simulations results are compared to multiple full-scale impact test data. The results indicate that all safety performance index such as vehicle trajectory, structural adequacy, occupant risk and dynamic deformation can be extracted from computer simulation and FEA results are coincident with those of tests with error less than 10%. Computer simulation method is proved to be highly feasible for safety performance evaluation of barriers. The concept that simulation models must be verified through tests is stressed and the suggestion that laws and regulations on professional audit and management of CAE engineers should be completed is brought out.

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Sun, Mingtao, and Ying Li. "Credit Risk Simulation of Enterprise Financial Management Based on Machine Learning Algorithm." Mobile Information Systems 2022 (October 11, 2022): 1–11. http://dx.doi.org/10.1155/2022/9007140.

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In the context of the rapid development of the Internet +, the e-commerce industry has developed very rapidly and is playing an increasingly important role in the market. More and more investors are also paying attention to the financial risks of the e-commerce industry. Therefore, how effectively identifying and controlling the credit risks of e-commerce enterprises corporate financial management is particularly important. Its financial-related business will be affected by various factors such as financing, credit, and the environment. The particle swarm optimization in the machine learning algorithm optimizes the support vector machine model; using its nonoverlapping clustering properties, it can fully display the density relationship between each data and the density relationship between its subclasses in a graphical way. It is hoped that the research on the financial risk of this enterprise can provide some insights into the identification, management, and related governance of the financial risk of e-commerce enterprises. In this context, this paper studies the credit risk simulation of corporate financial management based on machine learning algorithms, aiming to provide a new research direction for the current subject of corporate financial management credit risk. This paper optimizes the support vector machine model in the machine learning algorithm, integrates it into the financial risk of the enterprise, and analyzes the convergence of the algorithm. The experimental sample selected a bad e-commerce platform owned by a company, and the data were collected from the financial statements released by the company from 2018 to 2021. The experimental results show that in 2018, the two platforms lost −151.80 and −223.45, respectively, and the B platform lost more. By 2021, both platforms have achieved profits, which are 244.76 and 241.71, respectively. However, in the past few years, platform B has achieved positive profit growth every year, and the growth rate is average, and the overall growth rate is higher than that of platform A. This shows the limitations of managers’ decision-making and also shows the importance of enterprises to adjust their strategies in a timely manner through market feedback. The study was well completed.

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Ariav, A., Y. Kahane, and C. S. Tapiero. "A pooled computer center as a risk management tool." Computers & Operations Research 16, no. 3 (January 1989): 207–16. http://dx.doi.org/10.1016/0305-0548(89)90022-1.

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Khalifa, G. E. A. "(A104) Simulation in Disaster and Emergency Medicine." Prehospital and Disaster Medicine 26, S1 (May 2011): s28—s29. http://dx.doi.org/10.1017/s1049023x11001063.

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SimulationAn activity or situation that produces conditions which are not real, but have the appearance of being real, used especially for testing something. Longman Dictionary of Contemporary English. Simulation has evolved over the centuries but has not been applied to medicine until the 20th century with the introduction of virtual reality and computers. Prior to the 20th century simulation took the forms of physical models and cadavers. With the introduction of flight simulation there was an effort to move similar approaches into medicine. This was pushed by the demands of minimally invasive surgery and the introduction of robotics in surgery. In the 21st century in addition to cognitive task analysis tools we are beginning to see the migration of advanced intelligence tools to simulation. We are just at the beginning of how we will use adversarial reasoning in the medical environment and in high risk time constrained situations like Emergency Medicine. The practitioner of emergency medicine is at high risk for errors because of multiple factors including high decision density, high levels of diagnostic uncertainty, high patient acuity, and frequent distractions. Some authors have suggested that instructing physicians in “cognitive forcing strategies” or “metacognition” will help reduce the amount of cognitive error in medical practice. It has been said ‘‘[There is an] ethical obligation to make all efforts to expose health professionals to clinical challenges that can be reasonably well simulated prior to allowing them to encounter and be responsible for similar real-life challenges.’' TYPES OF SIMULATION • Verbal • Tactile • Visual • Situational • Environmental TYPES OF SIMULATION TRAINING • Standardized patients (role play) • Basic models (partial task trainers) • Simple level • Higher level • Mannequins • Low fidelity • High fidelity • Virtual patients • Screen-based; computer-based • COMBINATIONS • Augmented sp encounters with technology • Crises management HUMAN PATIENT SIMULATION • Realistic • Suitable for all levels • Safe • Wide variety of training programs • Expensive ADVANTAGES OF SIMULATION • Patients are never at risk • Serious but infrequent events, in predictable times and places • Errors can be allowed to occur, and play-out • Rehearsal, repetition, mastery • Crisis management simulation, planning • Reduces institutional liability • Increases operational confidence • Produces rapid results • Allows team training • Increases institutional prestige The use of high fidelity simulations to train multidisciplinary teams in critical environments is well established.

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Ji, Hong Ying. "Computer Control to Manage Risk of Pedestrian Head Crash Management Systems Based-High Risky Spots." Applied Mechanics and Materials 321-324 (June 2013): 1982–85. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1982.

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The right panel drawing direction is an important prerequisite for generating qualified parts, an important step before the panel forming simulation is to determine the reasonable direction of the drawing. Manually adjust parts in order to overcome rely on experience, the drawbacks to the drawing direction, the direction of the drawing punch and forming the contact area of the sheet as the goal of Computer Control determination Shortest Path Method. Objective function of the direction of the drawing for the variable contact area in the drawing direction of the feasible region, the use of heritage Shortest Path Methods to optimize the objective function of the contact area and, ultimately feasible within the contact area corresponding to the drawing direction, that is the best drawing direction. The measured results show that the direction of the drawing based on genetic Shortest Path Method, the Computer Control Shortest Path Method can fast and accurate to obtain the optimal direction of drawing.

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Robinson, Stewart, and Neil Higton. "Computer simulation for quality and reliability engineering." Quality and Reliability Engineering International 11, no. 5 (1995): 371–77. http://dx.doi.org/10.1002/qre.4680110508.

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Hoag, Dana L. K., and Jay Parsons. "Risk Navigator SRM: An Applied Risk Management Tool." Journal of Probability and Statistics 2010 (2010): 1–17. http://dx.doi.org/10.1155/2010/214358.

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Risk Navigator SRM is a ten-step risk management program for agricultural producers, which is based on the strategic planning process. The ten steps are designed to integrate disparate and difficult risk management concepts into a single system that is easy to use, yet still effective. With the aid of computers and the internet, producers can work through each step toward a final comprehensive plan. The website includes 25 decision tools that help producers accomplish each step and provides links to complementary educational programs, like a national agricultural risk education library, the award-winning risk management simulation program called Ag Survivor, and a recently published book that describes the program and provides additional depth and explanations. The ten-step program has been presented in over 200 workshops with over 90 percent approval by participants. The website has averaged over 1,000 unique visitors per month from 120 countries.

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Zheng, Liyan. "Risk Management of New Cosmetic Product Development Based on Data Management of Visualization in Scientific Computing." Scientific Programming 2022 (April 11, 2022): 1–10. http://dx.doi.org/10.1155/2022/5665208.

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With the continuous development of the social economy, people pay more and more attention to their own protection and maintenance, especially the quality of commodities in terms of usage of the commodity. As commonly used commodities, the quality of their new products in cosmetics is extremely important. In the rapidly developing cosmetics industry, in view of these needs and limitations, the data management method of visualization in scientific computing is introduced in this paper. Multiple risk factors in cosmetics development are established and sorted from the three perspectives of cosmetics development, production, and sales, by combining the new cosmetic product development process. The biggest risks are clarified, the corresponding cosmetic product risk assessment model is constructed, and the new cosmetic product development risk strategy and related management are realized. The simulation experiment results show that the data management method of visualization in scientific computing is effective and can support the risk management of new cosmetic product development.

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Matzner, Nils, and Robert Herrenbrück. "Simulating a Climate Engineering Crisis." Simulation & Gaming 48, no. 2 (November 30, 2016): 268–90. http://dx.doi.org/10.1177/1046878116680513.

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Background. At the 2015 Paris Agreement to limit global warming to a maximum of 2 degrees, climate activists and researchers began to look for alternative measures. Climate engineering (CE) - the deliberate manipulation of the planetary environment to decelerate climate change - emerges as a possibly effective, albeit risky and conflictual, option. Aim. This article aims both at simulating a plausible international scenario of negotiation over solar climate engineering deployment, and at utilizing the rules of Model United Nations (MUN) for collaborative learning in a university class. Furthermore, the article intends to provide a framework for simulations about CE that could easily be reproduced. Method. MUN is an established and well-tested foundation for a simulation with students, including preparation leading up to the simulation and feedback rounds afterwards. We repeated the simulation three times, recorded the sessions as well as the debriefings, and gathered interesting insight by comparing the results. Result. For our CE simulations, we discovered: 1. Divergent interests (e.g. global north vs global south). 2. Power struggle (e.g. role of the veto powers). 3. Scientific and political ignorance (e.g. decision-making under uncertainty). 4. Risk politics (e.g. trade-offs between climate change risks vs. CE risks). Conclusion. MUN qualifies well for simulating a CE crisis. However, known lacks in MUN settings (like underrepresentation of non-state actors) must be discussed during the debriefing. These simulations illustrate possible future conflicts over CE without being prescriptive in any way.

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Gilfedder, T. H., and B. K. Jones. "Computer simulation of fast electromigration lifetime determination techniques." Quality and Reliability Engineering International 9, no. 6 (November 1993): 519–24. http://dx.doi.org/10.1002/qre.4680090608.

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Kaliszewski, A. B. "RESERVOIR SIMULATION FOR RESERVOIR MANAGEMENT." APPEA Journal 26, no. 1 (1986): 397. http://dx.doi.org/10.1071/aj85034.

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The Hutton reservoir in the Merrimelia Field (Cooper-Eromanga Basin) was the subject of a 3-D reservoir simulation study. The primary objective of the study was to develop a reservoir management tool for evaluating the performance of the field under various depletion options.The study confirmed that the ultimate oil recovery from this strong water drive reservoir was not adversely affected by increasing total fluid offtake rate. However, any decisions regarding changes to the depletion scheme such as increasing production rates, if based solely on computer simulation results, should be viewed with caution. Careful monitoring of any changes to the depletion philosophy and checking of actual data against simulation predictions are essential to ensure that oil production rate and ultimate recovery are optimised.The model assisted in evaluating the economics of development drilling. While the simulation results are dependent on the validity of geological mapping, the model was useful in confirming that, due to very high transmissibility in the Hutton reservoir, additional wells would only accelerate production rather than increase ultimate recovery. The issue of drilling wells thus became one of balancing the benefits of accelerating production against the geological risk associated with that well.Interaction between the reservoir engineer and various disciplines, particularly development geology, is critical in the development and application of a good working simulation model. This was found to be especially important during the history matching phase in the study. If engineers and development geologists can learn more of the others' discipline and appreciate the role that each has to play in simulation studies, the validity of such models can only be improved.The paper addresses a number of the pitfalls commonly encountered in application of reservoir simulation results.

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Wang, Yingchao, Chen Yang, and Hanpo Hou. "Risk management in perishable food distribution operations." Industrial Management & Data Systems 120, no. 2 (October 5, 2019): 291–311. http://dx.doi.org/10.1108/imds-03-2019-0149.

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Purpose The purpose of this paper is to predict or even control the food safety risks during the distribution of perishable foods. Considering the food safety risks, the distribution route of perishable foods is reasonably arranged to further improve the efficiency of cold chain distribution and reduce distribution costs. Design/methodology/approach This paper uses the microbial growth model to identify a food safety risk coefficient to describe the characteristics of food safety risks that increase over time. On this basis, with the goal of minimizing distribution costs, the authors establish a vehicle routing problem with a food safety Risk coefficient and a Time Window (VRPRTW) for perishable foods. Then, the Weight-Parameter Whale Optimization Algorithm (WPWOA) which introduces inertia weight and dynamic parameter into the native whale optimization algorithm is designed for solving this model. Moreover, benchmark functions and numerical simulation are used to test the performance of the WPWOA. Findings Based on numerical simulation, the authors obtained the distribution path of perishable foods under the restriction of food safety risks. Moreover, the WPWOA can significantly outperform other algorithms on most of the benchmark functions, and it is faster and more robust than the native WOA and avoids premature convergence. Originality/value This study indicates that the established model and the algorithm are effective to control the risk of perishable food in distribution process. Besides, it extends the existing literature and can provide a theoretical basis and practical guidance for the vehicle routing problem of perishable foods.

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Peel, Michael, and Nick Wilson. "NEURAL NETWORK SIMULATION: A NEW APPROACH TO RISK ASSESSMENT AND BUSINESS FORECASTING." Management Research News 19, no. 6 (June 1, 1996): 50–54. http://dx.doi.org/10.1108/eb028477.

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Neural Networks (NN's), one of the latest developments in computer software artificial intelligence, are an innovative method of simulating and analysing complex and changing systems of relationships. Originally developed to mimic the neural architecture and functioning of the human brain, NN techniques have recently been applied successfully in a wide variety of complex business and financial applications (Trippi and Turban, 1994).

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Alfarisi, Salman, and Nico Surantha. "Risk assessment in fleet management system using OCTAVE allegro." Bulletin of Electrical Engineering and Informatics 11, no. 1 (February 1, 2022): 530–40. http://dx.doi.org/10.11591/eei.v11i1.3241.

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The purpose of this study is to use the OCTAVE allegro methodology to identify risks in fleet management system (FMS), determine prioritized risks to be mitigated, provide mitigation recommendations for these prioritized risks, and shows how effective the recommendation is. The result of this study is expected to become an input for FMS service provider of possible risks in FMS services, and risk mitigation approaches that can be used to handle those risks. This risk assessment has successfully identified 6 critical information assets, 10 risks in total, and 4 risks that need to be mitigated, followed by proposed mitigation approaches for those risks. Some of the recommendation has been applied by the company and contribute to SLA achievement of the system. The result also showed that application and simulation software provide most prominent risks in FMS service, thus securing these two will eliminate most risk in FMS service.

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Tang, Enlin. "Research on Interest Rate Risk of Housing Mortgage Loan Based on Computer Simulation." Computational Intelligence and Neuroscience 2021 (August 23, 2021): 1–6. http://dx.doi.org/10.1155/2021/6035022.

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In recent years, with the rapid increase of the business volume of housing mortgage loans of commercial banks, the risk of prepayment is increasingly exposed. Prepayment will have a great impact on the duration and convexity of housing mortgage loans of commercial banks and then bring difficulties to the asset liability management of banks. Therefore, empirical research on the changes of duration and convexity of housing mortgage loans caused by prepayment when the market interest rate changes is of great significance for commercial banks to manage interest rate risk exposure. Based on the analysis of the option characteristics of prepayable housing mortgage loan, the CIR model with GARCH(1, 1) is selected to describe the interest rate change path, and the computer simulation method is used to calculate OAS and then calculate the effective duration and effective convexity of housing mortgage loan under different prepayment rates, so as to understand the interest rate risk of housing mortgage loan in the presence of embedded option.

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Stockle, Claudio O. "GIS and simulation technologies for assessing cropping systems management in dry environments." American Journal of Alternative Agriculture 11, no. 2-3 (September 1996): 115–20. http://dx.doi.org/10.1017/s0889189300006895.

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AbstractThe long-term productivity, sustainability, and environmental impact of cropping systems cannot be assessed adequately using conventional agronomic experiments. This pap erdiscusses the use of computer-based technologies as support tools for this type of assessment, including crop growth simulation models, weather generators, geographical information systems, and risk assessment and economic models. Comprehensive systems that integrate these technologies are just emerging, offering great potential for the analysis of agricultural systems in the future.

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Glasserman, Paul, Wanmo Kang, and Perwez Shahabuddin. "Fast Simulation of Multifactor Portfolio Credit Risk." Operations Research 56, no. 5 (October 2008): 1200–1217. http://dx.doi.org/10.1287/opre.1080.0558.

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Chen, Wei, and Yuansheng Jiang. "Application of Markov Model-Based IoT in Agricultural Insurance and Risk Management." Mobile Information Systems 2021 (August 26, 2021): 1–8. http://dx.doi.org/10.1155/2021/8723258.

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As the foundation of the national economy, agriculture is a high-risk, weak industry. Affected by many factors, agricultural production is subject to catastrophe risks from time to time. Agricultural production is mainly faced with two major threats, natural disaster risk and market risk. As an effective risk management tool, the production and promotion of agricultural insurance have played an essential role in guaranteeing the development of the agricultural industry in some developed countries and major agricultural countries in the world. This article combines the Internet of Things and Markov model for agricultural insurance risk management. First, we combine the structure of the Internet of Things and select relevant statistical data. Then, we build a panel data system, starting from two perspectives in different regions and analyze agricultural insurance’s current development and characteristics at each stage. In addition, we use the Markov model to build a panel data model to explore the specific impact mechanisms deeply. We also study the effects of disaster risk levels in different regions on the development of agricultural insurance. After simulation verification, we believe that this model can effectively promote the balanced regional development of agricultural insurance.

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Zhou, Ming Shi. "Algorithm Realization of GUI Visualization Window Based on Numerical Simulation of Matlab." Applied Mechanics and Materials 556-562 (May 2014): 3868–71. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3868.

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This paper uses EVA investment objective function and benefits to establish the risk assessment model of enterprise investment and financing combination, and expounds the specific processes of computer EVA investment and financing risk management and designs the elimination matrix algorithm. In order to validate the validity and reliability of risk assessment model designed in this paper, the third part has designed numerical simulation of MATLAB, and an enterprise's 2011-2013 financial statements is took as an example to assess enterprise investment and financing risk. It can find that through calculation, the calculation error can achieve good convergence effects in 20s, and obtain the MATLAB GUI visualization window of enterprise investment and financing EVA accounting. It can identify enterprise year EVA profit value by using visualization window, which provides theoretical reference for enterprises investment and financing risk management.

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Rao, Yongcai, and Chunli Feng. "Analysis of Real-Time Early Warning Algorithm of Environmental Risk of Air Pollutants Based on Computer Simulation Technology." Mobile Information Systems 2022 (June 7, 2022): 1–6. http://dx.doi.org/10.1155/2022/4747149.

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In order to monitor the air pollutants in the living environment in real time, the computer simulation technology is used to monitor the air pollutants, and the weighted algorithm is used to warn the pollutants exceeding a certain content, so as to facilitate the air quality control. Air is an essential element for everyone’s survival. With the development of manufacturing industry, air quality has deteriorated sharply, which has a certain impact on human ecological environment and does harm to residents’ health. When more and more attention is paid to environmental problems, the state has issued corresponding measures to monitor air quality and formulate air quality indicators. Once an element in the air is found to exceed the standard, an alarm will be issued, which is convenient for management and detection. This study analyzes the risk early warning algorithm of pollutants in the air through computer simulation technology to realize the management of air quality. Lay the foundation for human living environment in the future.

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Marzhan, Yesmagambetova, Keribayeva Talshyn, Koshekov Kairat, Belginova Saule, Alibekkyzy Karlygash, and Ospanov Yerbol. "Smart technologies of the risk-management and decision-making systems in a fuzzy data environment." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 3 (October 7, 2022): 1463. http://dx.doi.org/10.11591/ijeecs.v28.i3.pp1463-1474.

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The purpose of this article is to provide a methodology for calculating and predicting the quality of solution implementation in complicated multi-parametric organizational and technological challenges with control agent uncertainty. The article's study findings are centered on the practical application of formal methods in predicting the outcomes of control and decision-making risks under the uncertainty of model agents. The proposed mathematics and simulation applications use a multi-agent strategy to handle the general problem of assessing quality control based on "producer risk (project customer)" and "user risk." Computer experiments with simultaneous graphical visualization of the results improve the accuracy of mathematical modeling, increasing the study's effectiveness. Under the uncertainty of system agents, a simulation model has been designed to analyze and anticipate the dependability of control and the hazards of decision-making. The suggested model is unique in that it takes into account the statistical nature of normative values as well as the rules of equal probability. To handle a frequent problem, the proposed system technique employs a dual approach. It accomplishes this by assessing the quality of the control process based on the magnitude of the risks in the decision-making system.

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Zhu, Helin, Joshua Hale, and Enlu Zhou. "Simulation optimization of risk measures with adaptive risk levels." Journal of Global Optimization 70, no. 4 (November 25, 2017): 783–809. http://dx.doi.org/10.1007/s10898-017-0588-8.

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Li, Chaoyu, Jun Ren, and Haiyan Wang. "A system dynamics simulation model of chemical supply chain transportation risk management systems." Computers & Chemical Engineering 89 (June 2016): 71–83. http://dx.doi.org/10.1016/j.compchemeng.2016.02.019.

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Tan, Qian. "Development of Automatic English Translation System Based on Fuzzy Matching and Software Simulation." Mobile Information Systems 2022 (July 20, 2022): 1–10. http://dx.doi.org/10.1155/2022/7795836.

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Software requirements are changeable, and the changes in requirements have led to many technical, economic, and management problems in the software development process, which are also considered to be the main source of software development risks. Based on the relationship between software requirements and design, this article analyzes the propagation process of requirement changes and the two dimensions of requirement change risk, opportunity and impact, and discusses software architecture customization that combines requirements, software architecture, and risk. On the basis of QFD and DSM, a composite relationship matrix is created according to requirements and software architecture, and two aspects of software architecture adaptability are analyzed from the perspective of the risk of changes in requirements. With the advent of the 5G era, this issue has gradually been paid attention to in its evolution. In order to further improve the intelligence level of the English translation system and improve the accuracy of English translation, this paper designs a translation algorithm that takes the changes in software requirements as the basis. On this basis, cross-compilation and multithreaded phrase translation loading methods are used to automate the translation system. System test results show that the system has high translation accuracy and good intelligence. Overall, the development of an automatic English translation system based on software change management and 5G networks will further enhance the intelligence and automation of English translation.

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Tong, Hui. "Maintenance of Network Security in Hospital Information Construction Based on the Internet of Things." International Transactions on Electrical Energy Systems 2022 (August 25, 2022): 1–10. http://dx.doi.org/10.1155/2022/3175786.

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With the continuous deepening of Chinese medical and health system reform, hospital informatization construction is advancing by leaps and bounds, especially in the context of “Internet of Things + Medical,” hospital informatization construction has made significant progress. However, computer network security management and maintenance work still face many contradictions and problems, and we need to pay attention to them. Based on the analysis of the current situation of computer network security management and maintenance in hospital information construction, this paper focuses on the problems of computer network security management and maintenance and proposes targeted optimization countermeasures. Based on the current problems faced by the medical industry in our country and the state’s support for the medical Internet of Things, this paper studies the application of the Internet of Things in hospital information management at home and abroad. This article uses hospital information network security maintenance evaluation methods and evaluation indicators to conduct an empirical analysis of the information security maintenance level of these 12 hospitals, from the risk assessment of hospital information network security, the establishment of strategies, the level of information security software and hardware equipment, and the information security personnel. Experiments show that 58.33% of the hospitals surveyed have only done part of the work on risk analysis and risk assessment of their own network information security, and 41.67% of the hospitals have not done this work at all. This shows that hospitals should incorporate computer network security management and maintenance into the information construction system, focusing on the outstanding problems and possible risks faced by the arm’s computer network security management and maintenance, and vigorously promote the reform and innovation of computer network security management and maintenance.

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He, Zhengqi, Dechun Huang, and Junmin Fang. "Social Stability Risk Diffusion of Large Complex Engineering Projects Based on an Improved SIR Model: A Simulation Research on Complex Networks." Complexity 2021 (December 26, 2021): 1–17. http://dx.doi.org/10.1155/2021/7998655.

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The development of China’s new urbanization has driven the rapid increase in large complex engineering projects, which have the characteristics of large-scale investment, long-term construction, and wide social influence, easily causing benefit conflicts among relevant stakeholders, and breaking out social stability risks. In the previous research, the risks of large complex engineering projects mainly concentrated on the assessment of economic risk, schedule risk, etc. However, there were few studies on social risks, and they did not consider how the risks spread on the complex networks based on the social connections such as interpersonal relationship. From the subject of social stability risk diffusion of large complex engineering projects, this paper constructs a related risk diffusion model based on the SIR model to analyze risk diffusion mechanism. Through NetLogo simulation platform, the model is placed under a small-world network environment that is closest to the topology structure of real social interpersonal relationship network for simulation research, aiming to find out key factors of social stability risk intervention for large complex engineering projects, which greatly contributes to the social stability risk management of large complex engineering projects.

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Lai, Hsin-hung. "Applicability of a Design Assessment and Management for the Current Ammunition Depots in Taiwan." Applied Sciences 10, no. 3 (February 4, 2020): 1041. http://dx.doi.org/10.3390/app10031041.

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In Taiwan, many ammunition depots have become outdated after having been in service for a long period of time, and if they are not properly managed, then accidental explosions might erupt inside. Leakage pressure after an explosion is closely related to the opening of the structure and the thickness of the wall. In order to reduce the risk of implosion, it is necessary to design a new structure or strengthen the existing ammunition libraries for the storage of ammunition required for combat. In order to evaluate the applicability of an existing ammunition depot design, making management simpler and safer, this study integrates the scale model experiment of an ammunition depot with computer simulation, the arbitrary Lagrangian–Eulerian (ALE) algorithm in ANSYS/LS-DYNA software, and it compares the results with the UFC3-340-02 specification in order to verify its applicability. The results show that computer simulation can verify that the data related to an implosion of an ammunition depot is similar to the specification. Therefore, the design results of the ammunition depot optimized by computer simulation can be used as a reference for the construction or strengthening of ammunition depots.

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Gao, Qian, Shanshan Guo, Xiaofu Liu, Gunasekaran Manogaran, Naveen Chilamkurti, and Seifedine Kadry. "Simulation analysis of supply chain risk management system based on IoT information platform." Enterprise Information Systems 14, no. 9-10 (July 24, 2019): 1354–78. http://dx.doi.org/10.1080/17517575.2019.1644671.

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Gorecki, Simon, Judicael Ribault, Gregory Zacharewicz, Yves Ducq, and Nicolas Perry. "Risk management and distributed simulation in Papyrus tool for decision making in industrial context." Computers & Industrial Engineering 137 (November 2019): 106039. http://dx.doi.org/10.1016/j.cie.2019.106039.

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Senthil, J., and M. Muthukannan. "Predication of construction risk management in modified historical simulation statistical methods." Ecological Informatics 66 (December 2021): 101439. http://dx.doi.org/10.1016/j.ecoinf.2021.101439.

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Xu, Wenpei, and Ting-Kwei Wang. "Dynamic safety prewarning mechanism of human–machine–environment using computer vision." Engineering, Construction and Architectural Management 27, no. 8 (July 16, 2020): 1813–33. http://dx.doi.org/10.1108/ecam-12-2019-0732.

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PurposeThis study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is capable of assessing nine safety indicators, which can be categorised into workers’ behaviour, environment and machine-related safety indicators, and the model is embedded in the safety prewarning system. The safety prewarning system can automatically extract safety information from surveillance cameras based on computer vision, assess risks based on the embedded comprehensive risk assessment model, categorise risks into five levels and provide timely suggestions.Design/methodology/approachFirstly, the comprehensive risk assessment model is constructed by adopting grey multihierarchical analysis method. The method combines the Analytic Hierarchy Process (AHP) and the grey clustering evaluation in the grey theory. Expert knowledge, obtained through the questionnaire approach, contributes to set weights of risk indicators and evaluate risks. Secondly, a safety prewarning system is developed, including data acquisition layer, data processing layer and prewarning layer. Computer vision is applied in the system to automatically extract real-time safety information from the surveillance cameras. The safety information is then processed through the comprehensive risk assessment model and categorized into five risk levels. A case study is presented to verify the proposed mechanism.FindingsThrough a case study, the result shows that the proposed mechanism is capable of analyzing integrated human-machine-environment risk, timely categorising risks into five risk levels and providing potential suggestions.Originality/valueThe comprehensive risk assessment model is capable of assessing nine risk indicators, identifying three types of entities, workers, environment and machine on the construction site, presenting the integrated risk based on nine indicators. The proposed mechanism, which adopts expert knowledge through Building Information Modeling (BIM) safety simulation and extracts safety information based on computer vision, can perform a dynamic real-time risk analysis, categorize risks into five risk levels and provide potential suggestions to corresponding risk owners. The proposed mechanism can allow the project manager to take timely actions.

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Roșca, Eugen, Serban Raicu, Mircea Roșca, and Florin Valentin Rusca. "Risks and Reliability Assessment in Maritime Port Logistics." Advanced Materials Research 1036 (October 2014): 963–68. http://dx.doi.org/10.4028/www.scientific.net/amr.1036.963.

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One of the most frustrating problems when dealing with risks it’s that they come in so many different forms. They can appear at any point in a port logistic system, they can interrupt the supply of raw materials or products, they can cause demand fluctuations (peak or collapse), inventory problems (lack or crowding), dispatch delay. Risks can range on a scale from small delay to a natural disaster, from short term to a permanent damage, with effects localized on a part of a supply chain or affecting the whole chain activity. The risk management allows port administration to take appropriate measures to reduce the consequences of a risk, to provide a good reliability of the logistic system or to design a resilient one. The paper investigates the major risks in port logistics and adequate measures to minimizing their effects. A risk management tree is set-up. Using computer simulation modelling, a case study investigates the port logistic system behaviour under different risk scenarios and evaluates the reliability of the system and its resilience. The operation capacity for different port logistics sub-system is assessed taking into consideration the required operating standards and the measures of performance (e.g. waiting time for vessels and transport vehicles, storage area and time for commodities) of the logistic system are computed.

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Zhang, Yang You, and Lin Zhang. "Optimization Simulation of Heuristic Algorithm in Supply Chain Based on Least Squares Support Vector Machine." Applied Mechanics and Materials 608-609 (October 2014): 660–64. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.660.

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This paper uses VB software and accounting information transparency to improve BOT investment mode and establishes computer accounting algorithm using the form of software programming. It also uses the least squares SCF criterion to improve this algorithm and gets the BOT investment accounting information platform after the optimization. The platform mainly focuses on openness of accounting information transparency and account investment efficiency and economic benefit of BOT investment mode using the form of computer array computing. At last, through the calculation, this paper concludes the convergence curve of risk aversion and economic efficiency and analyzes the benefits of BOT investment in risk management and supply chain which provides a theoretical reference for the study of accounting information transparency.

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Yu, Kai, Sai Zhang, Pingping Liu, Lujie Zhou, and Jing Chen. "Research on Simulation and Decision-Making of Coal Mine Workers’ Behavior Risk." Mathematics 10, no. 18 (September 11, 2022): 3297. http://dx.doi.org/10.3390/math10183297.

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The behavior risk of workers is one of the main restricting factors in coal mine safety decision-making and management. In this paper, the behavior and decision-making process of individuals and organizations are modeled and analyzed to solve this challenge, based on data analysis and behavior decision-making. Based on system dynamics (SD), this paper proposes an unsafe behavior correction system (SD-Ipt) for coal miners to reduce occupational risk. The “1 + 1 + 3 + X” behavior risk correction decision-making system is constructed, and the implementation scheme of the system is put forward, which has been applied in coal mines. This study can effectively correct the unsafe behavior of coal mining enterprises and improve the occupational safety and health management ability of coal mining enterprises.

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Zhupley, I. V. "Simulation modeling for sustainable development of production activities of an agricultural enterprise under risk conditions." IOP Conference Series: Earth and Environmental Science 981, no. 3 (February 1, 2022): 032012. http://dx.doi.org/10.1088/1755-1315/981/3/032012.

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Abstract The study examines the problem of using the ideology of imitation modeling in the management of the agricultural enterprise under risk conditions; a schematic diagram of the simulation model of the company’s production activities is presented; basic requirements, postulates, properties, constructs and model equations. The proposed model is adapted to the branch specifics of agriculture; structural consists of several interconnected settlement blocks using an algorithm for determining the wealthy production. Formulated directions for further research: creating a simulation model program for a computer, extension and clarification of the constructs and equations of the model to account for regional specificity

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Li, Changzhi, Shuaijie Li, and Xiaotao Cheng. "Flood Risk Assessment in Fujian Province, China." Journal of Disaster Research 7, no. 5 (October 1, 2012): 567–72. http://dx.doi.org/10.20965/jdr.2012.p0567.

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Flood risk assessment is important for decisionmaking in flood management strategies and countermeasures. In this paper, an index systemincluding one integrated index, three component indices, and eight basic indices is first introduced. Then a simple model based on the index system is formulated for assessing flood risks in the mid- and macro-scale regions. Two methods, namely Normal Distribution Reference and Hazard-Vulnerability Block, are used thereafter to define threshold values of risk levels. A macrostrategy for flood management is finally developed based on computed flood risk levels. A case study was carried out for flood risk assessment at the county level in Fujian province, China, and simulation results matched with local relief and historical flood records well.

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Faruq, Shaik Umar, Yalamanjula Venkata Archan, and Maddikera Lokanath Reddy. "Risk Assessment and Management of Underground Metro Construction (Bengaluru Scenario)." International Journal of Innovative Technology and Exploring Engineering 11, no. 8 (July 30, 2022): 33–42. http://dx.doi.org/10.35940/ijitee.h9155.0711822.

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Construction projects are characterized as very complex projects, where uncertainties are part of it. Risk is an uncertain event or condition that, if it occurs, has a positive or a negative impact on one or more project objectives, such as time, cost, scope or quality. Risk management includes the process concerned with the conducting the risk identification, analysis, responses and management planning and control on a project The study aims at carrying out the risk assessment and management process in the construction of Bangalore Underground Metro project. At first, the risks associated with the project and also with the similar projects in past are identified and listed based on the historic reviews, interviews and literature review. A questionnaire survey is prepared for the risks that are listed and probability and impact of these risks on the projects are found out, and risks are prioritized based on the risk index score which forms the probability-impact matrix and risk register is formed. A schedule is prepared in Primavera P6, and then integrated with Primavera Risk Analysis (PERT Master) software which analyze the schedule for the risk events assigned to the activities and for the defined probability distributions and then schedule of the project is simulated using the Monte Carlo simulation for the both pre mitigated and the post mitigated analysis, and then results are compared. Response strategies are suggested for the moderate to higher priorities risks.

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Qin, Yu Ping. "Application of Virtual Reality Technology in Construction Control and Management." Applied Mechanics and Materials 427-429 (September 2013): 2851–54. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.2851.

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The virtual reality is an advanced technology in the modern man-made environment. A three-dimensional virtual reality world is produced by computer simulation to make users feel as if they were personally on the scene. By building the virtual model and virtual construction process, construction control and management based on the virtual reality system can be used to improve efficiency of project management and construction, ensure construction progress, save cost, improve safety and reduce engineering risk, so as to provide guidance for engineering construction.

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Barot, C., D. Lourdeaux, J. M. Burkhardt, K. Amokrane, and D. Lenne. "V3S: A Virtual Environment for Risk-Management Training Based on Human-Activity Models." Presence: Teleoperators and Virtual Environments 22, no. 1 (February 2013): 1–19. http://dx.doi.org/10.1162/pres_a_00134.

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As work situations become more complex, virtual reality has proven to be advantageous for the emerging needs in risk-management training. However, building perfectly realistic simulations of the technical systems is not enough to address complex coactivity situations, where human factors play an important part. There is a need for virtual environments that would put trainees into varied ecological situations, inducing knowledge and competencies that would be put into practice in genuine work situations. The V3S project was proposed to build a generic framework for tailor-made virtual environments that can adapt to different application cases, technological configurations, or pedagogical strategies. This framework relies on the integration of multiple explicit models (domain, activity, and risk model). In order to build ecologically valid virtual environments, these models represent not only the prescribed activity, but the situated knowledge of operators about their tasks, including deviations from the procedures. These models are used both to monitor learners' actions, detecting errors and compromises; and also to generate virtual characters' behaviors, subject to erroneous actions. Moreover, dynamic situated feedback allows for progressive learning scenarios, adapting the complexity of the situations to the learner's activity and level. Evaluations have shown a high satisfaction level and encouraging usability measures. In future work, we propose to extend the possibilities of the simulation through the creation and monitoring of adaptive scenarios, adjusting the behavior of virtual characters able to assist or disrupt the user.1

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Zinkhan, George M., Erich A. Joachimsthaler, and Thomas C. Kinnear. "Individual Differences and Marketing Decision Support System Usage and Satisfaction." Journal of Marketing Research 24, no. 2 (May 1987): 208–14. http://dx.doi.org/10.1177/002224378702400207.

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Relatively little is known about how managers interact with marketing decision support systems such as a computer simulation. The authors investigate individual difference variables to determine their role in influencing the utilization of and satisfaction with one component of a marketing decision support system. The research vehicle used is a computer simulation model for assisting decision making in retailing. The findings indicate that risk averseness, involvement, cognitive differentiation, and age are important predictors of utilization and satisfaction. Managerial implications of the findings are discussed.

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Cesare, M., J. C. Santamarina, C. J. Turkstra, and E. Vanmarcke. "Risk-based bridge management: optimization and inspection scheduling." Canadian Journal of Civil Engineering 21, no. 6 (December 1, 1994): 897–902. http://dx.doi.org/10.1139/l94-095.

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Bridge management based on reliability methods permits the selection of the set of repair projects that minimizes the total network risk in a planning horizon. This approach, previously proposed by the authors, uses the Markovian model for the decay of structural components, evaluates the overall reliability of the bridge as a system, and computes risk by taking into consideration the consequences of reduced function. This paper presents important additional aspects of risk-based bridge management. First, genetic algorithms are proposed as an alternative optimization strategy; small and large bridge networks are solved, guiding the solution towards minimum risk. Second, Markovian transition matrices for deterioration and post-inspection Bayesian updating are combined to schedule inspections so that the overall reliability of the bridge network is maximized for a given inspection budget. Results from a simulation study using a real bridge network are presented and compared with current inspection practice. Key words: bridge management, reliability, risk assessment, optimization, inspection scheduling.

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Journal articles on the topic 'Risk management Computer simulation'

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