Optimal -k nearest neighbours based ensemble for classification and feature selection in chemometrics data

Haq, Inzamam ul; Khan, Dost Muhammad; Hamraz, Muhammad; Iqbal, Nadeem; Ali, Amjad; Khan, Zardad

doi:10.1016/j.chemolab.2023.104882

Cited by 4 publications

(1 citation statement)

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“…KNN operates based on the principle of finding the most similar items or users in a dataset to make predictions. The output value for a test case is determined based on the majority vote or averaging of the output values of its k-nearest neighbors in the training data [ 41 ]. By considering multiple neighbors, KNN takes into account the local structure of the data and can provide robust predictions.…”

Section: Methodsmentioning

confidence: 99%

Knowledge graph and CBR-based approach for automated analysis of bridge operational accidents: Case representation and retrieval

Xu,

Wei,

Cai

et al. 2023

PLoS ONE

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Bridge operational accident analysis is a critical process in bridge operational risk management. It provides valuable knowledge support for responding to newly occurring accidents. However, there are three issues: (1) research specifically focused on the past bridge operational accidents is relatively scarce; (2) there is a lack of mature research findings regarding the bridge operational accidents knowledge representation; and (3) in similar case retrieval, while case-based reasoning (CBR) is a valuable approach, there are still some challenges and limitations associated with its usage. To tackle these problems, this research proposed an automated analysis approach for bridge operational accidents based on a knowledge graph and CBR. The approach includes case representation and case retrieval, leveraging advancements in computer science and artificial intelligence. In the proposed approach, the case representation involves the adoption of a knowledge graph to construct multi-dimensional networks. The knowledge graph captures the relationships between various factors and entities, allowing for a comprehensive representation of accidents domain knowledge. In the case retrieval, a multi-circle layer retrieval strategy was innovatively proposed to enhance retrieval efficiency. Three target cases were randomly selected to verify the validity of the proposed methodology. The combination of a knowledge graph and CBR can indeed provide useful tools for the automated analysis of bridge operational accidents. Additionally, the proposed methodology can serve as a reference for intelligent risk management in other types of infrastructures.

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Section: Methodsmentioning

confidence: 99%