A pattern-based validation method for the credibility evaluation of simulation models

SIMULATION ◽  
2019 ◽  
Vol 96 (2) ◽  
pp. 151-167
Author(s):  
Yuanjun Laili ◽  
Lin Zhang ◽  
Yongliang Luo
Keyword(s):  
Simulation Model ◽  
Dynamic Models ◽  
Reference Data ◽  
Model Performance ◽  
Simulation Models ◽  
Validation Method ◽  
Evaluation Procedures ◽  
Serial Data ◽  
Multi Agent

Measuring the credibility of a simulation model has always been challenging due to its growing uncertainty and complexity. During the past decades, plenty of metrics and evaluation procedures have been developed for evaluating different sorts of simulation models. Most of the existing research focuses on the direct comparison of numerical results with a group of reference data. However, it is sometimes unsuitable for evolving dynamic models such as the multi-agent models. With the same condition, both the practical system and the simulation model perform highly dynamic actions. The credibility of the model with insufficient information, non-stationary states and changing environment is unable to acquire through a direct pair comparison. This paper presents a pattern-based validation method to complementarily extract hidden patterns that exist in both a simulation model and its reference data, and assess the model performance in a different aspect. Firstly, multi-dimensional perceptually important points strategy is modified to find the patterns exist in time-serial data. Afterward, a pattern organizing topology is applied to automatically depict required pattern from reference data and assess the performance of the corresponding simulation model. The extensive case study on three simulation models shows the effectiveness of the proposed method.

scholarly journals Output Signal Power Analysis in Erbium-Doped Fiber Amplifier with Pump Power and Length Variation Using Various Pumping Techniques

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
S. Semmalar ◽  
S. Malarkkan
Keyword(s):  
Pump Power ◽  
Simulation Model ◽  
Output Signal ◽  
Model Performance ◽  
Simulation Models ◽  
Fiber Amplifier ◽  
Length Variation ◽  
Signal Power ◽  
Erbium Doped Fiber Amplifier ◽  
Erbium Doped

The scope of this paper is to analyze the output signal power with pump power and length variation in cascaded EDFA simulation model performance. This paper describes the simulation model of Erbium-Doped Fiber Amplifier (EDFA) of variable lengths (10 m, 50 m, and 120 m) with dual pumping techniques (dual forward pumping with two 980 nm wavelengths, dual forward and backward pumping with two 980 nm wavelengths) and Tri-pumping techniques. The simulation models consist of input source and pump power coupled by WDM coupler which gives optimized signal power in the above-mentioned simulation model. The simulation model consists of source with multiple wavelengths (1520 nm–1618 nm), pumping source with the wavelength 980 nm, isolator, and filter. The resulting models accurately represent EDFA optimized output signal power. Simulation results show that choosing careful fiber length 120 m and pump power 1 W in dual pumping provided 0.07 W optimized output signal power compared to other pumping techniques.

Stratified Constraint Satissfaction Networks in Synergetic Multi-Agent Simulations of Language Evolution

2007 ◽  
pp. 140-175 ◽  
Author(s):  
Alexander Mehler
Keyword(s):  
Language Learning ◽  
Simulation Model ◽  
Language Evolution ◽  
Self Regulation ◽  
Simulation Models ◽  
Communication Processes ◽  
Multi Agent ◽  
Level I ◽  
The One ◽  
System Variables

We describe a simulation model of language evolution which integrates synergetic linguistics with multi-agent modelling. On the one hand, this enables the utilization of knowledge about the distribution of the parameter values of system variables as a touch stone of simulation validity. On the other hand, it accounts for synergetic interdependencies of microscopic system variables and macroscopic order parameters. This approach goes beyond the classical setting of synergetic linguistics by grounding processes of self-regulation and self-organization in mechanisms of (dialogically aligned) language learning. Consequently, the simulation model includes four level, (i) the level of single information processing agents which are (ii) dialogically aligned in communication processes enslaved (iii) by the social system in which the agents participate and whose countless communication events shape (iv) the corresponding language system. In summary, the present paper is basically conceptual. It outlines a simulation model which bridges between different levels of language modelling kept apart in contemporary simulation models. This model relates to artificial cognition systems in the sense that it may be implemented to endow an artificial agent community in order to perform distributed processes of meaning constitution.

Method to Control Manufacturing Cell by Driving Simulation Model

2014 ◽  
Vol 8 (4) ◽  
pp. 539-549 ◽  
Author(s):  
Hironori Hibino ◽  
Keyword(s):  
Simulation Model ◽  
Manufacturing System ◽  
Simulation Models ◽  
Driving Simulation ◽  
Manufacturing Cell ◽  
Manufacturing Management ◽  
Execution Phase ◽  
Manufacturing Engineering ◽  
Wiring System

In this paper, a method to Control a Manufacturing Cell by Driving Simulation Models (CMC-DSM) is proposed. The purposes of CMC-DSM is not only to directly operate the manufacturing cell while controlling and monitoring the manufacturing cell based on a simulation model in the manufacturing system execution phase, but also to support the manufacturing engineering processes based on the simulation model. In the manufacturing engineering processes, the simulation model is mixed and synchronized with real equipment and management applications in the case where parts of equipment and manufacturing management applications are not provided in the manufacturing cell. In the manufacturing system execution phase, when the simulation model acts in response to manufacturing system behaviors, the manufacturing system is controlled by synchronizing the simulation model behaviors. In this paper, the Environment required to Control a Manufacturing Cell by Driving Simulation Models (E-CMC-DSM) is proposed. The necessary functions for E-CMC-DSM are defined and developed. E-CMC-DSM consists of a simulator developed to drive simulation models (EMU), a soft-wiring system developed in this study, and a semi-standard industrial network middleware. The validation of ECMC-DSM was carried out through a case study.

Application of an Interactive Water Simulation Model in urban water management: a case study in Amsterdam

2014 ◽  
Vol 70 (11) ◽  
pp. 1729-1739 ◽  
Author(s):  
J. G. Leskens ◽  
M. Brugnach ◽  
A. Y. Hoekstra
Keyword(s):  
Water Management ◽  
Simulation Model ◽  
Simulation Models ◽  
Decision Makers ◽  
Urban Water ◽  
Urban Water Management ◽  
Current Water ◽  
Water Simulation ◽  
Computation Algorithms

Water simulation models are available to support decision-makers in urban water management. To use current water simulation models, special expertise is required. Therefore, model information is prepared prior to work sessions, in which decision-makers weigh different solutions. However, this model information quickly becomes outdated when new suggestions for solutions arise and are therefore limited in use. We suggest that new model techniques, i.e. fast and flexible computation algorithms and realistic visualizations, allow this problem to be solved by using simulation models during work sessions. A new Interactive Water Simulation Model was applied for two case study areas in Amsterdam and was used in two workshops. In these workshops, the Interactive Water Simulation Model was positively received. It included non-specialist participants in the process of suggesting and selecting possible solutions and made them part of the accompanying discussions and negotiations. It also provided the opportunity to evaluate and enhance possible solutions more often within the time horizon of a decision-making process. Several preconditions proved to be important for successfully applying the Interactive Water Simulation Model, such as the willingness of the stakeholders to participate and the preparation of different general main solutions that can be used for further iterations during a work session.

scholarly journals Rapid-cycle systems modeling to support evidence-informed decision-making during system-wide implementation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
R. Christopher Sheldrick ◽  
Gracelyn Cruden ◽  
Ana J. Schaefer ◽  
Thomas I. Mackie
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Implementation Strategy ◽  
Simulation Models ◽  
Illustrative Case ◽  
Systems Modeling ◽  
Cycle Systems ◽  
Analytic Strategy ◽  
Group Interviews

Abstract Background To “model and simulate change” is an accepted strategy to support implementation at scale. Much like a power analysis can inform decisions about study design, simulation models offer an analytic strategy to synthesize evidence that informs decisions regarding implementation of evidence-based interventions. However, simulation modeling is under-utilized in implementation science. To realize the potential of simulation modeling as an implementation strategy, additional methods are required to assist stakeholders to use models to examine underlying assumptions, consider alternative strategies, and anticipate downstream consequences of implementation. To this end, we propose Rapid-cycle Systems Modeling (RCSM)—a form of group modeling designed to promote engagement with evidence to support implementation. To demonstrate its utility, we provide an illustrative case study with mid-level administrators developing system-wide interventions that aim to identify and treat trauma among children entering foster care. Methods RCSM is an iterative method that includes three steps per cycle: (1) identify and prioritize stakeholder questions, (2) develop or refine a simulation model, and (3) engage in dialogue regarding model relevance, insights, and utility for implementation. For the case study, 31 key informants were engaged in step 1, a prior simulation model was adapted for step 2, and six member-checking group interviews (n = 16) were conducted for step 3. Results Step 1 engaged qualitative methods to identify and prioritize stakeholder questions, specifically identifying a set of inter-related decisions to promote implementing trauma-informed screening. In step 2, the research team created a presentation to communicate key findings from the simulation model that addressed decisions about programmatic reach, optimal screening thresholds to balance demand for treatment with supply, capacity to start-up and sustain screening, and availability of downstream capacity to provide treatment for those with indicated need. In step 3, member-checking group interviews with stakeholders documented the relevance of the model results to implementation decisions, insight regarding opportunities to improve system performance, and potential to inform conversations regarding anticipated implications of implementation choices. Conclusions By embedding simulation modeling in a process of stakeholder engagement, RCSM offers guidance to realize the potential of modeling not only as an analytic strategy, but also as an implementation strategy.

scholarly journals 3DGIS-Based Multi-Agent Geosimulation and Visualization of Building Evacuation Using GAMA Platform

2014 ◽  
Vol XL-2 ◽  
pp. 87-91 ◽  
Author(s):  
E. G. Macatulad ◽  
A. C. Blanco
Keyword(s):  
Spatial Data ◽  
Simulation Models ◽  
Building Evacuation ◽  
Agent Based ◽  
Gis Applications ◽  
3D Space ◽  
The People ◽  
Multi Agent ◽  
Traditional Approaches

Recent GIS applications have already extended analyses from the traditional 2-2.5D environment (x,y,attributes) to 3D space (x,y,z,attributes). Coupled with agent-based modeling (ABM), available 3DGIS data can be used to develop simulation models for improved analysis of spatial data and spatial processes. One such application is on building evacuation for which ABM is integrated with 3D indoor spatial data to model human behavior during evacuation events and simulate evacuation scenarios visualized in 3D. The research presented in this paper develops a multi-agent geosimulation model for building evacuation, integrating 3DGIS dataset of the case study building as input in ABM using the GAMA simulation platform. This model is intended to complement and improve traditional approaches in building evacuation planning and management such as earthquake and fire drills. The initial model developed includes PEOPLE agents to model the building occupants, and FLOORS, ROOMS, INDOOR_PATHS and EXIT_POINTS agents, which are modeled from the 3DGIS layers. The INDOOR_PATHS and EXIT_POINTS agents influence the movement of PEOPLE agents. Test simulations were performed involving PEOPLE agents placed in rooms of the building based on potential number of occupants computed based from the floor area of each room. The PEOPLE agents are programmed to find the shortest path along the INDOOR_PATHS towards the EXIT_POINTS instance designated for each room of the building. The simulation computes for the total time it takes for all PEOPLE agents to exit the building.

scholarly journals The Introduction to System Dynamics Approach to Operational Efficiency and Sustainability of Dry Port’s Main Parameters

2019 ◽  
Vol 11 (8) ◽  
pp. 2413 ◽  
Author(s):  
Dmitri Muravev ◽  
Aleksandr Rakhmangulov ◽  
Hao Hu ◽  
Hengshuo Zhou
Keyword(s):  
System Dynamics ◽  
Simulation Models ◽  
Operational Efficiency ◽  
Continuous Increase ◽  
Flexible Planning ◽  
Multi Agent ◽  
Practical Tool ◽  
Set Up ◽  
Dry Ports

The continuous increase of trade between China and Europe brought congestion problems at major Chinese seaports. An effective way to solve this issue is to set up intermodal terminals often called dry ports. However, the dynamics of various influenced factors on dry port’s implementation calls for the adaptive and flexible planning of the terminal. This paper analyzes the shortcomings of previous research related to the dry port’s implementation from the perspective of the applied numerous parameters concerning evaluating its operational efficiency and sustainability. The operational efficiency and sustainability of a dry port are evaluated by the developed system of the main parameters. This system gives the understanding of how these parameters are interrelated between each other and fills the gap in studies of inverse interrelations between main parameters of a dry port. To fully understand the sustainability of the main parameters of a dry port, this paper puts forward the simulation models description of the developed system. The developed model is a practical tool to evaluate the reliability of hypotheses about the functional interrelations between the main parameters of the dry port, as well as to evaluate the sustainability of the system. Finally, in order to develop functional interrelations between main parameters, the data from several Chinese dry ports has been collected. Finally, the developed multi-agent system dynamics model has been validated in the case study of Yiwu dry port located in Zhejiang, China.

Stratified Constraint Satisfaction Networks in Synergetic Multi-Agent Simulations of Language Evolution

2008 ◽  
pp. 107-136
Author(s):  
Alexander Mehler
Keyword(s):  
Language Learning ◽  
Simulation Model ◽  
Language Evolution ◽  
Simulation Models ◽  
Communication Processes ◽  
Distributed Processes ◽  
Multi Agent ◽  
The One ◽  
System Variables ◽  
Parameter Values

We describe a simulation model of language evolution which integrates synergetic linguistics with multiagent modelling. On the one hand, this enables the utilization of knowledge about the distribution of the parameter values of system variables as a touch stone of simulation validity. On the other hand, it accounts for synergetic interdependencies of microscopic system variables and macroscopic order parameters. This approach goes beyond the classical setting of synergetic linguistics by grounding processes of selfregulation and self-organization in mechanisms of (dialogically aligned) language learning. Consequently, the simulation model includes four layers, (i) the level of single information processing agents which are (ii) dialogically aligned in communication processes enslaved (iii) by the social system in which the agents participate and whose countless communication events shape (iv) the corresponding language system. In summary, the present chapter is basically conceptual. It outlines a simulation model which bridges between different levels of language modelling kept apart in contemporary simulation models. This model relates to artificial cognition systems in the sense that it may be implemented to endow an artificial agent community in order to perform distributed processes of meaning constitution.

scholarly journals Some Issues in the Testing of Computer Simulation Models

2016 ◽  
Vol 5 (1) ◽  
pp. 1-10
Author(s):  
David Murray-Smith
Keyword(s):  
Simulation Model ◽  
Model Validation ◽  
Simulation Models ◽  
Model Testing ◽  
Model Verification ◽  
Verification And Validation ◽  
Quality Data ◽  
Model Quality ◽  
Face Validation

The testing of simulation models has much in common with testing processes in other types of application involving software development. However, there are also important differences associated with the fact that simulation model testing involves two distinct aspects, which are known as verification and validation. Model validation is concerned with investigation of modelling errors and model limitations while verification involves checking that the simulation program is an accurate representation of the mathematical and logical structure of the underlying model. Success in model validation depends upon the availability of detailed information about all aspects of the system being modelled. It also may depend on the availability of high quality data from the system which can be used to compare its behaviour with that of the corresponding simulation model. Transparency, high standards of documentation and good management of simulation models and data sets are basic requirements in simulation model testing. Unlike most other areas of software testing, model validation often has subjective elements, with potentially important contributions from face- validation procedures in which experts give a subjective assessment of the fidelity of the model. Verification and validation processes are not simply applied once but must be used repeatedly throughout the model development process, with regressive testing principles being applied. Decisions about when a model is acceptable for the intended application inevitably involve some form of risk assessment. A case study concerned with the development and application of a simulation model of a hydro-turbine and electrical generator system is used to illustrate some of the issues arising in a typical control engineering application. Results from the case study suggest that it is important to bring together objective aspects of simulation model testing and the more subjective face- validation aspects in a coherent fashion. Suggestions are also made about the need for changes in approach in the teaching of simulation techniques to engineering students to give more emphasis to issues of model quality, testing and validation.

Verification and Validation of Pipeline Terminal Simulation Models

2014 ◽  
Author(s):  
Frank Lin ◽  
Allan Chegus ◽  
Dumitru Cernelev
Keyword(s):  
Simulation Model ◽  
Simulation Models ◽  
Difficult Problem ◽  
Verification And Validation ◽  
Optimization Software ◽  
Simulation And Optimization ◽  
Terminal Performance ◽  
Model Validity ◽  
Complex Simulation

The problem of validating a complex simulation model represents pipeline terminal performance with verifiable accuracy is a difficult problem requiring extensive testing and calibration. This paper discusses a case study of the verification and validation of a terminal simulation model. The approach to deciding model validity is presented as well as the process of verifying and validating the model including methodology and thresholds for acceptance. Ultimately the paper demonstrates the ability of commercial simulation and optimization software to work collaboratively to determine an optimal business solution.

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