Optimal road accident case retrieval algorithm based on <i>k</i>-nearest neighbor

Dong, Xianyuan; Lu, Maixin

doi:10.1177/1687814018824523

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…The emphasis is on the selection, optimization and improvement of the weight distribution method. These include information entropy (Dong and Lu 2019), gray correlation (Ha et al 2020), genetic algorithm (Kwon et al 2019), neural network (Yan et al 2019) and other methods.…”

Section: Similarity Measurementioning

confidence: 99%

“…However, NN cannot fully meet the retrieval requirements for complex large-scale data. Therefore, NN is often combined with other algorithms (Dong and Lu 2019;Mulyim and Arcos 2020) to improve the retrieval accuracy and efficiency. Although purely similarity-based retrieval is still the most widely used technology, the limitations of similarity are gradually exposed with the development of CBR.…”

Section: Case Retrievalmentioning

confidence: 99%

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A review of the development and future challenges of case-based reasoning

Yan

Cheng

2023

Preprint

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Case-based reasoning (CBR), which is based on the cognitive assumption that similar problems have similar solutions, is an important problem-solving and learning method in the field of artificial intelligence. In this article, the development of CBR is mainly reviewed, and the major challenges of CBR are summarized. The paper is organized into four parts. First, the basic framework and concepts of CBR are introduced. Then, the developed technology and innovative work that were formed in solving problems by CBR are summarized. Moreover, the application fields of CBR are sorted. Finally, according to the idea of deep learning and interpretable artificial intelligence, the main challenges for the future development of CBR are proposed.

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Section: Similarity Measurementioning

confidence: 99%

Section: Case Retrievalmentioning

confidence: 99%

A review of the development and future challenges of case-based reasoning

Yan

Cheng

2023

Preprint

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“…Ma et al [24] combined information entropy with principal component analysis to trace gridded taxi driving trajectories in space and extracted different patterns using a K-means clustering method. Dong et al [25] determined the weights of features related to accidents based on the K-nearest neighbor algorithm and an information entropy index and built a retrieval database for road accident cases using a two-step clustering algorithm. Sun et al [26] classified road segments based on the 24-h emission rates by using the temporal fuzzy C-means (FCM) clustering, while geographical detector and Moran's I were introduced to verify the impact of built environment on line source emissions and the similarity of emissions generated from the nearby road segments.…”

Section: Related Researchmentioning

confidence: 99%

Mining Taxi Pick-Up Hotspots Based on Grid Information Entropy Clustering Algorithm

Liu

Wang

et al. 2021

Journal of Advanced Transportation

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In view of the fact that the density-based clustering algorithm is sensitive to the input data, which results in the limitation of computing space and poor timeliness, a new method is proposed based on grid information entropy clustering algorithm for mining hotspots of taxi passengers. This paper selects representative geographical areas of Nanjing and Beijing as the research areas and uses information entropy and aggregation degree to analyze the distribution of passenger-carrying points. This algorithm uses a grid instead of original trajectory data to calculate and excavate taxi passenger hotspots. Through the comparison and analysis of the data of taxi loading points in Nanjing and Beijing, it is found that the experimental results are consistent with the actual urban passenger hotspots, which verifies the effectiveness of the algorithm. It overcomes the shortcomings of a density-based clustering algorithm that is limited by computing space and poor timeliness, reduces the size of data needed to be processed, and has greater flexibility to process and analyze massive data. The research results can provide an important scientific basis for urban traffic guidance and urban management.

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“…Guo et al [5] used the retrieval strategy based on the classification strategy, combined fuzzy clustering, and compared various research strategies to optimize the retrieval strategy. Dong and Lu [6] constructed a traffic management assistance system by using field matching and a K-nearest neighbor retrieval strategy, combined with CBR technology. Xu et al [7] coordinated the risk management of bridge operation based on the retrieval strategy combining knowledge graph and CBR.…”

Section: Introductionmentioning

confidence: 99%

Research on case retrieval strategy based on drawing die of automobile coverings

Cheng,

Qi,

Guo

2024

J. Phys.: Conf. Ser.

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To improve the accuracy and efficiency of case retrieval in the process of intelligent design of automobile panel drawing die, this paper proposes a case retrieval strategy based on model reasoning and an improved k-nearest neighbor (KNN) method. Through the functional representation and modular description of the existing knowledge of automobile panel drawing die design, the problems to be solved are compared with the model, and the preliminary screening is completed. Then the nearest neighbor algorithm is used to realize the retrieval, and the subjective and objective weight assignment method is used to optimize the retrieval strategy. The subjective weight uses the improved three-scale analytic hierarchy process to avoid the subjectivity increase caused by the judgment matrix’s artificial adjustment. The objective weight uses the grey wolf optimization algorithm, and the dynamic adaptive calculation of the average similarity is designed to enhance the reliability of the fitness function. Finally, the case retrieval of the drawing die during the design of a certain type of panel die is taken as an example to test. The retrieval strategy can accurately complete the retrieval of historically similar cases, which verifies the effectiveness of the proposed instance retrieval strategy.

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Optimal road accident case retrieval algorithm based on k-nearest neighbor

Cited by 7 publications

References 6 publications

A review of the development and future challenges of case-based reasoning

A review of the development and future challenges of case-based reasoning

Mining Taxi Pick-Up Hotspots Based on Grid Information Entropy Clustering Algorithm

Research on case retrieval strategy based on drawing die of automobile coverings

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