Intelligent simulation of aquatic environment economic policy coupled ABM and SD models

Wang, Huihui; Zhang, Jiarui; Zhang, Weihua

doi:10.1016/j.scitotenv.2017.09.184

Cited by 26 publications

(13 citation statements)

References 39 publications

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“…Regarding the water resources of Yangtze River Economic Belt, scholars have conducted fruitful research, mainly exploring the water ecological footprint [30,31], utilization efficiency [32], green efficiency [33,34] and carrying capacity [35] of water resources. Lots of the research has focused on water resource efficiency [6] and carrying capacity [24], but little on sustainable use of water resources. Most of the indicators are based on the pressure-state-response (PSR) framework [36], less on indicators for scientific and technological innovation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Most of the indicators are based on the pressure-state-response (PSR) framework [36], less on indicators for scientific and technological innovation. Measurement is mainly performed using principal component analysis [37], improved analytic hierarchy process [38], fuzzy comprehensive evaluation [39,40], grey relational analysis [41], data envelopment analysis (DEA) [42], system dynamics [6,43], technique for order preference by similarity to ideal solution (TOPSIS) [44,35] and back propagation (BP) neural network [45]. However, there are few ways to measure the degree of interaction between subsystems in the water resources sustainability system, and most scholars have undertaken their research on water resources in the Yangtze River Economic Belt from nine provinces and two municipalities, while the research from the urban level is quite rare in this regard.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Regarding the water resources of Yangtze River Economic Belt, scholars have conducted fruitful research. Most of the existing research focused on water resource efficiency [6] and carrying capacity [24], but less on the sustainability and coupling coordination of urban water resources in the YREB. The water sustainability of cities is affected by the interaction of economic, social, environmental and technological subsystems.…”

Section: Introductionmentioning

confidence: 99%

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Urban Water Inclusive Sustainability: Evidence from 38 Cities in the Yangtze River Economic Belt in China

Gao

Guo

2021

Sustainability

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The ecological environment of urban water resources in the Yangtze River Economic Belt (YREB) is in a huge challenge; yet, while myriad studies have investigated the carrying capacity or sustainable utilization of Chinese water resources, few to none have looked at the inclusive sustainable development of water resources. In this article, a new concept of urban water inclusive sustainability (UWIS) is firstly proposed, and the conceptual framework of ASFII and a five-dimensional indicator system are developed, integrating availability, sustainability, friendliness, inclusiveness and innovation. The panel data of 38 cities in the YREB are adopted from 2008 to 2018 to measure UWIS and five development indexes by the TOPSIS (technique for order preference by similarity to ideal solution) and entropy method. Moreover, the characteristics of the temporal–spatial evolution of the overall system and subsystems coupling coordination are described using the coupling coordination degree model. Key factors that hinder UWIS are identified through the obstacle degree model. The results indicate that the overall UWIS showed a gradual upward trend at a lower to medium level from 2008 to 2018 and a friendliness > sustainability > inclusiveness > innovation > availability index. The UWIS from high to low is YRDUA (Yangtze River Delta urban agglomeration), MRYRUA (middle reaches of the Yangtze River urban agglomeration) and CCUA (Chengdu–Chongqing urban agglomeration). The 38 cities are in low-level coordination, and their temporal characteristics show a trend of economy > science and technology > water resources > environment > societal system, YRDUA > MRYRUA > CCUA. The spatial differentiation is manifested as high in the east and low in the west. The main obstacles come from 12 factors, such as the water resources utilization rate, etc. The findings of our study will be a scientific reference for the Chinese government to track UWIS and ensure urban water resources security in the YREB.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Urban Water Inclusive Sustainability: Evidence from 38 Cities in the Yangtze River Economic Belt in China

Gao

Guo

2021

Sustainability

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“…There have been extensive studies on the use of ABM to solve complex social phenomenon globally. Wang et al used ABM to examine the environmental consequences and economic impacts of water resource shortages under variant economic policies in Dianchi Lake Basin in China [8]. A complex system model was proposed to simulate the impact of alternative economic policies on water use and pricing.…”

Section: Agent-based Modellingmentioning

confidence: 99%

Analysing Road Traffic Situation in Lilongwe: An Agent Based Modelling (ABM) Approach

Sibale

Munthali

2021

Adv. J. Grad. Res.

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A 15, 451 km road network forms the main mode of transport for Malawi with 26 % paved. With increasing number of vehicles and elongated travel times during rush hour the study analysed the traffic situation on the M1 road between Mchinji and Area 18 roundabouts in Lilongwe City using an agent-based model (ABM). The methodology used game theory’s traffic grip model to analyse traffic flow by controlling traffic variables such as lights, speed limits and the number of vehicles. Each intersection was treated as non-cooperative game where each agent tried to minimize its queue resulting into Q−Nash’s equilibrium as the solution. The ABM tested the empirical relationships of traffic flow parameters in terms of density, ﬂow, acceleration, deceleration, speed, time lost in traffic congestion and fuel consumption. The model was calibrated using traffic data collected through observing 1,312 vehicles sampled against 24,977. The observation results from the road junctions reveal that on average, a vehicle takes 20 mins 18 seconds, 37 minutes 6 seconds, 44 minutes 21 seconds and 58 minutes 53 seconds to exit Chitukuko, Bwandilo, Chilambula roads and Area 18 roundabout respectively upon entering the M1 at Mchinji roundabout. This data was then used to calibrate the business-as-usual model for the peak hour scenario for the road junctions. The model results show that a selected vehicle entering Chitukuko junction travels at an average speed of 22.60 km/hr, until it exits that junction. On average the selected motorists spend 2.52 l/km with a traffic density of 72 v/km. If dualized average speeds improved to 41.54 km/hr while the traffic density declined to 54.42 v/km, saving motorists MK 3,921,624.00 annually. The predictive model of the dual carriage informed that by 2021, commuters will spend MK 5,187,168 on fuel more than single-lane business as usual scenario of 2019.

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“…By contrast, as a bottom-up approach, the ABM can capture the heterogeneity of agents at the individual level but has limitations in modeling the macro system [26,46]. As evidenced by previous studies on the consumer choice behaviors of sustainable products [46,47], the diffusion process of innovative technologies [48], and the impact of alternative economic policies on water use and pricing [49], the different mechanisms of SD and ABM mean that they can have complementary roles and, therefore, achieve a better understanding of complex systems [26]. Nasirzadeh et al [50] have developed an SD-ABM simulation model to investigate the social influence on safety violations.…”

Section: Literature Reviewmentioning

confidence: 99%

Understanding the Social Contagion Effect of Safety Violations within a Construction Crew: A Hybrid Approach Using System Dynamics and Agent-Based Modeling

Liang

Lin

Zhang

2018

IJERPH

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Previous research has recognized the importance of eliminating safety violations in the context of a social group. However, the social contagion effect of safety violations within a construction crew has not been sufficiently understood. To address this deficiency, this research aims to develop a hybrid simulation approach to look into the cognitive, social, and organizational aspects that can determine the social contagion effect of safety violations within a construction crew. The hybrid approach integrates System Dynamics (SD) and Agent-based Modeling (ABM) to better represent the real world. Our findings show that different interventions should be employed for different work environments. Specifically, social interactions play a critical role at the modest hazard levels because workers in this situation may encounter more ambiguity or uncertainty. Interventions related to decreasing the contagion probability and the safety–productivity tradeoff should be given priority. For the low hazard situation, highly intensive management strategies are required before the occurrence of injuries or accidents. In contrast, for the high hazard situation, highly intensive proactive safety strategies should be supplemented by other interventions (e.g., a high safety goal) to further control safety violations. Therefore, this research provides a practical framework to examine how specific accident prevention measures, which interact with workers or environmental characteristics (i.e., the hazard level), can influence the social contagion effect of safety violations.

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Intelligent simulation of aquatic environment economic policy coupled ABM and SD models

Cited by 26 publications

References 39 publications

Urban Water Inclusive Sustainability: Evidence from 38 Cities in the Yangtze River Economic Belt in China

Urban Water Inclusive Sustainability: Evidence from 38 Cities in the Yangtze River Economic Belt in China

Analysing Road Traffic Situation in Lilongwe: An Agent Based Modelling (ABM) Approach

Understanding the Social Contagion Effect of Safety Violations within a Construction Crew: A Hybrid Approach Using System Dynamics and Agent-Based Modeling

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