Improving Air Quality in Communities by Using a Multicriteria Decision-Making Model Based on Big Data: A Critical Review

Hsueh, S. L.; Cheng, Ai-Chih

doi:10.15666/aeer/1502_015031

Cited by 10 publications

(2 citation statements)

References 39 publications

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“…With the rapid development of information technology, the accumulated data has practical application value in scientific research, commercial development, decision-making reference, environmental protection, etc. The accumulated data has value in practical applications of scientific research, commercial development, decision-making reference, environmental protection, and other topics [4]. This paper can obtain the development status of carbon accounting, carbon sequestration, and carbon trading by analyzing the relevant big data, which can be used to analyze a large amount of data related to carbon emissions and identify opportunities for organizations to reduce their carbon footprint.…”

Section: Introductionmentioning

confidence: 99%

Construction of carbon-neutral data governance framework in the context of big data

Pan

Hong

et al. 2023

E3S Web of Conf.

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Climate change has brought increasingly serious challenges to human survival and sustainable development. It is a global consensus to achieve carbon peak and carbon neutrality as soon as possible to protect the earth's home. To provide the latest research frontier of the carbon-neutral data governance framework in the new era, this study uses VOSviewer and bibliometrics to systematically review the carbon-neutral data governance framework related to carbon trading, carbon accounting, carbon storage, and carbon pricing based on the mapping of 141 documents retrieved from the Web of Science (WoS） database from 1900 to 2023, integrating international data space, data sovereignty, and E-liability. It mainly analyzes four parts: annual trend, main countries, and sources, keyword co-occurrence, and thematic strategic coordinate map, and summarizes the research results using the concepts of system thinking and knowledge intermediary, aiming to provide some references for researchers, managers, and industry professionals.

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Section: Introductionmentioning

confidence: 99%

Construction of carbon-neutral data governance framework in the context of big data

Pan

Hong

et al. 2023

E3S Web of Conf.

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“…From the operational point of view, multi-criteria methods have the ability to adapt to problems on several fronts, which can be described as conflicting interests. Although the multi-criteria evaluation technique does not solve the problem, it can help detail the problem, making the complex situation more transparent for decision makers (Munda et al, 1994;Hsueh and Cheng, 2017).…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Logic Model for Zone Delineation in a Preservation Area in Brazil

Tambarussi¹,

Wilhelm²,

Magalhães³

et al. 2019

Appl. Ecol. Env. Res.

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Territorial planning plays a fundamental role in preservation of areas for ecological conservation and environmental management as well as in providing adequate spaces for visitation and research and prioritizing sustainable relationships between man and nature. The present work exhibits a methodological proposal that allows the standardization of territorial classifications in preservation areas. Based on fuzzy logic, the proposed model observes the particularities of a preservation area; hence, the decision generated in the classification of zones represents the work that is currently being developed in the areas of biology, geography, environmental engineering, among other research groups. The modeling combines the evaluation of the data collected in the field (variables: quantitative and qualitative) with vegetation indices obtained from satellite imagery. Combining this information enables each sampling point to be categorized, thereby generating preservation area zones. The results showed that the methodology can distinguish border areas as transition zones, allowing appropriate management to offer detailed information of the study area. The case study, in which the methodology was applied in a preservation area in southern Brazil, showed that the methodology assists in territorial planning, with a clear indication of what actions have been performed and simple data collection.

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Data Asset Quality Evaluation Framework Based on a Hybrid Multi‐Criteria Decision‐Making Method

Xu,

You,

Yang

et al. 2024

Quality & Reliability Eng

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This study presents a new framework for evaluating data asset quality using a hybrid multi‐criteria decision‐making (MCDM) approach that integrates the decision making trial and evaluation laboratory (DEMATEL), best–worst method (BWM), and fuzzy‐technique for order of preference by similarity to the ideal solution (TOPSIS) techniques. First, the framework considers data as both a product and an asset, leading to the development of quality indicators beyond the traditional dimensions. Subsequently, the interrelationships among indicators are addressed using the DEMATEL method, allowing for the identification of key indicators that significantly influence data asset quality in a given scenario. The BWM method is then employed to determine the weights of these key indicators, enabling a more precise assessment of their importance. After that, the TOPSIS method, incorporating triangular fuzzy numbers, is utilized to rank the data asset quality of different companies. Finally, the effectiveness of the framework is demonstrated by applying it to a group of companies, and the results of the company's evaluation are discussed, along with the corresponding data asset quality improvement initiatives.

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Improving Air Quality in Communities by Using a Multicriteria Decision-Making Model Based on Big Data: A Critical Review

Cited by 10 publications

References 39 publications

Construction of carbon-neutral data governance framework in the context of big data

Construction of carbon-neutral data governance framework in the context of big data

A Fuzzy Logic Model for Zone Delineation in a Preservation Area in Brazil

Data Asset Quality Evaluation Framework Based on a Hybrid Multi‐Criteria Decision‐Making Method

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