Browsing by Author "Liu, Shiyong"

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    Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research
    Liu, Shiyong; Triantis, Konstantinos P.; Zhao, Li; Wang, Youfa (PLOS, 2018-04-25)
    Background In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. Methodology In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. Results In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. Conclusions This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment. This research can help practitioners and decision makers to gain better understanding on the dynamics and complexities of precision intervention in healthcare. It can aid the improvement of the optimal allocation of resources for targeted group (s) and the achievement of maximum utility. As this technology becomes more mature, one can design policy flight simulators by which policy/intervention designers can test a variety of assumptions when they evaluate different alternatives interventions.
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    The Design of an Urban Roadside Automatic Sprinkling System: Mitigation of PM2.5–10 in Ambient Air in Megacities
    Liu, Shiyong; Triantis, Konstantinos P.; Zhang, Lan (Hindawi, 2014-07-23)
    The objective of this research paper is to describe the system architecture for an urban roadside automatic mist-generating system. Its primary purpose is to mitigate particulate matter especially PM2.5–10. In this paper, four graphs are provided to exhibit the constituent elements of this system. This paper also discusses the functional extensions of this system for alternative uses in civil engineering which include winter road deicing and desnowing with added salt; clean-up of street dust; lowering of temperature of a “hot island” during the summer; the addition of humidity in an arid area; and the suppression of flu virus in the winter season. The structure and function of this system are comprehensively discussed in this paper. This system is compared to existing and other proposed systems in terms of control options, efficiency, and primary functional issues. The unique design of the road automatic sprinkling system renders itself a prominent option. Although there are no data available for this conceptual system, some expected qualitative and quantitative outcomes are provided and justified. The paper concludes with some potential research areas and challenges associated with this system architecture.
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    Three Essays on Travel Demand Management Strategies for Traffic Congestion Mitigation
    Liu, Shiyong (Virginia Tech, 2007-12-07)
    This dissertation provides three essays. In the first essay, a model with two linguistic variables is built to demonstrate the joint effect of multiple linguistic variables in a dynamic modeling context. Triangular membership function is used to represent the linguistic variables and the joint effect is captured through fuzzy inference method. In this essay, the results obtained by employing fuzzy concepts are compared with the results that one would obtain using generic lookup functions. The second essay develops a system dynamics model by which policy makers can assess the impact of various travel demand management interventions within a metropolitan area and as a consequence understand the complex behavior of affected transportation-socioeconomic systems. This essay builds on a previously formulated approach where fuzzy concepts are used to represent five linguistic variables used in the model. We also compare the level of traffic congestion under the scenarios with and without traffic congestion pricing. The third essay is based on the second essay where different scenarios of the travel demand management policies are evaluated and analyzed. There are two parts in this essay. The first part addresses the construction of a Management Flight Simulator (MFS) that is used to do policy analysis for travel demand management policies. By using the Management Flight Simulator, the second part of the essay describes the evaluation of alternative travel demand management policies. In this research, we found that the revenue generated from congestion pricing does increase mass transit capacity even with the aging of mass transit capacity. However, in the short term traffic congestion is mitigated while in the long term the proposed travel demand management policy actually deteriorates the traffic situation.