Air Quality level Assessment through the Grey Clustering Analysis on Lima, Peru

2019 ◽  
Author(s):  
Alexi Delgado ◽  
Andres Aguirre
Keyword(s):  
Air Quality ◽  
Clustering Analysis ◽  
Quality Level ◽  
Grey Clustering

scholarly journals A Comprehensive Real-Time Indoor Air-Quality Level Indicator

2016 ◽  
Vol 8 (9) ◽  
pp. 881 ◽  
Author(s):  
Jungho Kang ◽  
Kwang-Il Hwang
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Real Time ◽  
Indoor Air ◽  
Quality Level ◽  
Level Indicator

Health status evaluation method of CNC machine tools based on grey clustering analysis and fuzzy comprehensive evaluation

2021 ◽  
pp. 1-18
Author(s):  
Xiaoqing Huang ◽  
Zhilong Wang ◽  
Shihao Liu
Keyword(s):  
Health Status ◽  
Clustering Analysis ◽  
Machine Tools ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Indicator System ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Grey Clustering

In order to solve the problem of health evaluation of CNC machine tools, an evaluation method based on grey clustering analysis and fuzzy comprehensive evaluation was proposed. The health status grade of in-service CNC machine tools was divided, and the performance indicator system of CNC machine tools was constructed. On the above basis, the relative importance of each performance and its indicators were combined, and grey clustering analysis and fuzzy comprehensive evaluation was utilized to evaluate the health status of in-service CNC machine tools to determine their health grade. The proposed health status evaluation method was applied to evaluate the health level of an in-service gantry CNC machine that can be used for the machining propellers, and the results shown that the health status of the whole gantry CNC machine tool is healthy. The proposed evaluation method provides useful references for further in-depth research on the health status analysis and optimization of CNC machine tools.

scholarly journals Research on the Evaluation Index System and the Grey Clustering Analysis Model of Teaching Quality of Physical Education in Higher Education

2015 ◽  
Vol 10 (8) ◽  
pp. 59 ◽  
Author(s):  
Baoquan Wu
Keyword(s):  
Physical Education ◽  
Clustering Analysis ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Colleges And Universities ◽  
Evaluation Index System ◽  
Analysis Model ◽  
Grey Clustering

Teaching quality evaluation of physical education usually involves multiple influence factors with grey and uncertain information. This brings about limitations to effective evaluation of teaching quality of physical education in colleges and universities. Thus, this paper draws merits from previous research and proposes a teaching quality evaluation system and model of physical education in colleges and universities. First, based on real situations, grey categories of evaluation state for physical education teaching quality are established. The definite weighted functions of grey category of evaluation state are confirmed. Specific steps of the teaching quality evaluation model based on grey clustering analysis are accounted for. Finally, a case study is introduced to verify the model. This model enlightens a new way to evaluate teaching quality of physical education in colleges and universities.

scholarly journals Promoting Pollution-Free Routes in Smart Cities Using Air Quality Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2507 ◽  
Author(s):  
Francisco Ramos ◽  
Sergio Trilles ◽  
Andrés Muñoz ◽  
Joaquín Huerta
Keyword(s):  
Quality Of Life ◽  
Air Quality ◽  
Smart Cities ◽  
Extensive Study ◽  
Current Work ◽  
Quality Level ◽  
Quality Indices ◽  
Big City ◽  
Precautionary Measures

Nowadays, citizens have a huge concern about the quality of life in their cities, especially regarding the level of pollution. Air quality level is of great importance, not only to plan our activities but also to take precautionary measures for our health. All levels of governments are concerned about it and have built their indexes to measure the air quality level in their countries, regions or cities. Taking into account the existing sensor infrastructure within smart cities, it makes possible to evaluate these indices and to know anywhere the level of pollution in real-time. In this scenario, the main objective of the current work is to foster citizens’ awareness about pollution by offering pollution-free routes. To achieve this goal, a technology-agnostic methodology is presented, which allows for creating pollution-free routes across cities depending on the level of pollution in each zone. The current work includes an extensive study of existing air quality indices, and proposes and carries forward to deployment of the defined methodology in a big city, such as Madrid (Spain).

scholarly journals THE EFFECTS OF ENVIRONMENTAL ISSUES ON RESIDENTIAL HOUSE PRICE (IN THE CASE OF ULAANBAATAR CITY)

2018 ◽  
pp. 117-130
Author(s):  
Oyunjargal D ◽  
Byambatseren Ch
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
House Price ◽  
Measurement Data ◽  
Quality Measurement ◽  
Air Quality Index ◽  
Quality Level ◽  
Average Price ◽  
Residential House ◽  
The Impact

The purpose of this research is to determine the impact of the environment, especially the quality of air on house price. In addition, it also includes the research of the linkage between the index of air quality and average price of residential house which located in the most crowded districts of Ulaanbaatar such as Bayangol, Bayanzurkh, Chingeltei, Sukhbaatar, Songinokhairkhan and Khan-Uul. The statistical analysis and statistics determination methods were applied to identify the relationship utilizing the air quality index, determined from the air quality measurement data recorded in 2015-2017, and the average price per square meter of newly built apartment houses in the selected districts. The research findings suggest that there is little direct link between the house prices and air quality level, and the air quality levels of Ulaanbaatar districts do not have a significant impact on the price per square meter. Therefore, the air quality index should not considered as a house price determinant.

scholarly journals The Grey Clustering Analysis for Photovoltaic Equipment Importance Classification

2017 ◽  
Vol 6 (2) ◽  
pp. 47
Author(s):  
Hongjiu LIU ◽  
Qin ZHANG
Keyword(s):  
Clustering Analysis ◽  
Maintenance Management ◽  
Analysis Model ◽  
Reliable Operation ◽  
Power Station ◽  
Analytic Hierarchy ◽  
Operation And Maintenance ◽  
Grey Clustering ◽  
Judgment Matrix ◽  
Hierarchy Process

The evaluation of equipment importance is an important part of the operation and maintenance management and its purpose is to identify the key equipment which has important influence on the reliable operation of the power station. On the basis of grey clustering theory, the paper firstly establishes the analysis model of photovoltaic (pv) power station equipment importance and the weights of factors in the target hierarchy is solved by using the judgment matrix in analytic hierarchy process. Secondly, according to the whitenization weight function of the grey clustering, pv equipment is classified into three types: key equipment, vital equipment and general equipment, which lays the foundation for the equipment maintenance strategy choice. Finally, an application example verifies the practicality and scientificity of the proposed method.

scholarly journals Spatio-Temporal Variation of Particulate Matter(PM2.5) Concentrations and Its Health Impacts in a Mega City, Delhi in India

2018 ◽  
Vol 12 ◽  
pp. 117863021879286 ◽  
Author(s):  
Amit Kumar Gorai ◽  
Paul B Tchounwou ◽  
SS Biswal ◽  
Francis Tuluri
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Environmental Protection Agency ◽  
Quality Index ◽  
Temporal Variations ◽  
Air Quality Index ◽  
Capital City ◽  
Health Impacts ◽  
Quality Level ◽  
Spatio Temporal

Rising concentration of air pollution and its associated health effects is rapidly increasing in India, and Delhi, being the capital city, has drawn our attention in recent years. This study was designed to analyze the spatial and temporal variations of particulate matter (PM2.5) concentrations in a mega city, Delhi. The daily PM2.5 concentrations monitored by the Central Pollution Control Board (CPCB), New Delhi during November 2016 to October 2017 in different locations distributed in the region of the study were used for the analysis. The descriptive statistics indicate that the spatial mean of monthly average PM2.5 concentrations ranged from 45.92 μg m−3 to 278.77 μg m−3. The maximum and minimum spatial variance observed in the months of March and September, respectively. The study also analyzed the PM2.5 air quality index (PM2.5—Air Quality Index (AQI)) for assessing the health impacts in the study area. The AQI value was determined according to the U.S. Environmental Protection Agency (EPA) system. The result suggests that most of the area had the moderate to very unhealthy category of PM2.5-AQI and that leads to severe breathing discomfort for people residing in the area. It was observed that the air quality level was worst during winter months (October to January).

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