Aircraft grouping based on improved divisive hierarchical clustering algorithm

Xia, Qingjun; Li, Xueming; Song, Ye Xin; Zhang, Baocheng

doi:10.1016/j.jairtraman.2014.07.002

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…, 2022). The improved split hierarchical clustering algorithm DHCA has better time efficiency than a dichotomy (Xia et al. , 2014).…”

Section: Index Classification and Stratificationmentioning

confidence: 99%

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Research on optimization of index system design and its inspection method: data quality diagnosis, index classification and stratification

Yin

Cao²,

Zhou³

et al. 2022

MAEM

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PurposeThe purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.Design/methodology/approachUsing modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.FindingsBased on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.Originality/valueThe innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

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“…, 2022). The improved split hierarchical clustering algorithm DHCA has better time efficiency than a dichotomy (Xia et al. , 2014).…”

Section: Index Classification and Stratificationmentioning

confidence: 99%

“…The fast hierarchical clustering HAC algorithm reduces the spacetime complexity and computation (Teymourian et al, 2022). The improved split hierarchical clustering algorithm DHCA has better time efficiency than a dichotomy (Xia et al, 2014).…”

Section: Cluster Analytic Hierarchy Processmentioning

confidence: 99%

Research on optimization of index system design and its inspection method: data quality diagnosis, index classification and stratification

Yin

Cao²,

Zhou³

et al. 2022

MAEM

View full text Add to dashboard Cite

show abstract

A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory

et al. 2022

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Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and increased complexity of aviation and has to be improved in order to maintain aviation safety. It is agreed that without significant improvement in this domain, the safety objectives defined by international organisations cannot be achieved and a risk of more incidents/accidents is envisaged. Nowadays, computer science plays a major role in data management and decisions made in ATM. Nonetheless, despite this, Artificial Intelligence (AI), which is one of the most researched topics in computer science, has not quite reached end users in ATM domain. In this paper, we analyse the state of the art with regards to usefulness of AI within aviation/ATM domain. It includes research work of the last decade of AI in ATM, the extraction of relevant trends and features, and the extraction of representative dimensions. We analysed how the general and ATM eXplainable Artificial Intelligence (XAI) works, analysing where and why XAI is needed, how it is currently provided, and the limitations, then synthesise the findings into a conceptual framework, named the DPP (Descriptive, Predictive, Prescriptive) model, and provide an example of its application in a scenario in 2030. It concludes that AI systems within ATM need further research for their acceptance by end-users. The development of appropriate XAI methods including the validation by appropriate authorities and end-users are key issues that needs to be addressed.

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Aircraft grouping based on improved divisive hierarchical clustering algorithm

Cited by 2 publications

References 8 publications

Research on optimization of index system design and its inspection method: data quality diagnosis, index classification and stratification

Research on optimization of index system design and its inspection method: data quality diagnosis, index classification and stratification

A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory

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