An environmental assessment model of construction and demolition waste based on system dynamics: a case study in Guangzhou

Liu, Jingkuang; Liu, Yedan; Wang, Xuetong

doi:10.1007/s11356-019-07107-5

Cited by 199 publications

(72 citation statements)

References 24 publications

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“… This research utilized system dynamics and coupled analysis to evaluate and simulate the HATC security level ( Table 1 ). According to Wang et al (2019) [ 98 ]’s classification criteria for coupling coordination types, this research classified security and warning levels as follows: we divided interval value (0, 0.4) into highly dangerous (HD), interval value (0.4, 0.7) into moderately dangerous (MD), interval value (0.7, 0.9) into low dangerous (LD), and interval value (>0.9) into slightly dangerous (SD).…”

Section: Methodsmentioning

confidence: 99%

Benign or disordered development? Assessment and simulation of security of highly aggregated tourist crowds in China

Yin

2020

PLoS ONE

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Arising with increasing security issues in highly aggregated tourist crowds (HATCs), widespread attention has been dedicated to security status. Assessing and forecasting the security status of HATCs in various situations related to tourist destinations is an important strategy of security management. Thus, this study constructed a system dynamic flow diagram for the security evaluation of HATCs. The relevant data were collected on perceptions of crowded tourists through questionnaires at Tianyou Peak during China's National Day (Golden Week Holiday). Additionally, efforts were made to conduct online surveys at Shanghai Disney Park and Shilin Night Market in Taipei, since crowding always occurs in these two areas. Empirical results based on Vensim software suggest that HATC status is the result of the coupling of various influencing factors and the result of the benign coupling of the three subsystems: multi-source pressure, state variation, and management response. HATC security presents a changing trend of “increase-decrease-recovery”. Differences exist in the changes of HATC security status in different spaces and at different time nodes. The findings also indicated that HATCs that appear in the daytime are more stable than HATCs that appear at special time nodes. This study highlighted that the security management of HATCs should focus on systematization, differentiation, and precision management.

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Section: Methodsmentioning

confidence: 99%

Benign or disordered development? Assessment and simulation of security of highly aggregated tourist crowds in China

Yin

2020

PLoS ONE

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“…It is well established that the cost and use of energy affect human lives every day. In this sense, many issues arise from the content of energy consumption such as acid rain, dependency on depleting supplies of fossil fuels, greenhouse gas emissions [8][9][10][11][12][13][14][15][16][17], climate change [18][19][20][21], as well as environmental concerns that come along with energy power supply [22][23][24][25][26][27][28][29][30][31][32][33][34][35]. In recent years, various techniques have been used for the optimal design of the HVAC system [36][37][38][39][40][41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

Suggesting a Stochastic Fractal Search Paradigm in Combination With Artificial Neural Network for Early Prediction of Cooling Load in Residential Buildings

Moayedi¹,

Mosavi²

2021

Preprint

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Early prediction of thermal loads plays an essential role in analyzing energy-efficient buildings' energy performance. On the other hand, stochastic algorithms have recently shown high proficiency in dealing with this issue. These are the reasons that this work is dedicated to evaluating an innovative hybrid method for predicting the cooling load (CL) in buildings with residential usage. The proposed model is a combination of artificial neural networks and stochastic fractal search (SFS-ANN). Two benchmark algorithms, namely the grasshopper optimization algorithm (GOA) and firefly algorithm (FA), are also considered to be compared with the SFS. The non-linear effect of eight independent factors on the CL is analyzed using each model's optimal structure. Evaluation of the results outlined that all three metaheuristic algorithms (with more than 90 % correlation) can adequately optimize the ANN. In this regard, this tool's prediction error declined by nearly 23, 18, and 36 % by applying the GOA, FA, and SFS techniques. Also, all used accuracy criteria indicated the superiority of the SFS over the benchmark schemes. Therefore, it is inferred that utilizing the SFS along with ANN provides a reliable hybrid model for the early prediction of CL.

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“…e intelligent building is characterized by the complete application and integration of advanced technologies in the fields of construction [1], control, information, artificial intelligence, and so on. It builds a comprehensive self-learning intelligent platform covering the whole building, provides people with sustainable and perfect function, the safety of buildings, and maximally improves the efficiency of buildings and the comfort of environment.…”

Section: Introductionmentioning

confidence: 99%

Indoor Environment Intelligent Control System of Green Building Based on PMV Index

Shao

2021

Advances in Civil Engineering

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With the development and progress of society, people have higher and higher requirements for indoor high temperature and humidity environment. The traditional air conditioning system uses temperature and humidity as control parameters, which has a single control goal, low comfort, and high energy consumption. The purpose of this study is to use predicted mean vote (PMV) thermal comfort index and green building to analyze the intelligent control system of indoor environment. Our intelligent research platform is a set of “intelligent” experimental platforms. The sample data were divided into human metabolic rate, human external work, and heat resistance of clothes, temperature, and air. According to the PMV value, velocity, relative humidity, and average radiation temperature are divided into three categories, which are composed of seven parameters. According to the survey results, PMV at 24°C fluctuates around 0.5, which is an important value for human thermal comfort, and people will feel more comfortable. When the temperature reaches 26°C, the PMV index will reach 0.6 or even more than 0.6, and the human body will be in an unpleasant state due to overheating. In addition, the higher the wind speed is, the smaller the PMV value is and the stronger the cooling effect is. The higher the temperature is, the smaller the influence of wind speed on PMV value is. In other words, the sensitivity of the human body to wind speed will be reduced. In this study, the PMV index intelligent control system can adjust the indoor environment properly, and the conclusion is that the energy consumption and use effect are superior to air conditioning equipment. This research has contributed to the development of intelligent buildings.

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An environmental assessment model of construction and demolition waste based on system dynamics: a case study in Guangzhou

Cited by 199 publications

References 24 publications

Benign or disordered development? Assessment and simulation of security of highly aggregated tourist crowds in China

Benign or disordered development? Assessment and simulation of security of highly aggregated tourist crowds in China

Suggesting a Stochastic Fractal Search Paradigm in Combination With Artificial Neural Network for Early Prediction of Cooling Load in Residential Buildings

Indoor Environment Intelligent Control System of Green Building Based on PMV Index

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