Jianyang Li’s research while affiliated with Hefei University of Technology and other places

... In the recommendation process, it calculates the recommendation score through the linear combination of emotional features and similarity, which is used for query-based and user-based recommendation scenarios. Li et al. [122] argued that, since users only interact with items of interest in the recommendation system, that system must retain very large amounts of personalized information and item sparsity, which seriously affects the performance of the recommendation system; therefore, they proposed a CBRrecommender method to reduce data sparsity through data classification and dynamic clustering, which makes the system run faster in large-scale recommendation research that dynamically calculates user preferences. ...

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A Review of the Development and Future Challenges of Case-Based Reasoning

... W.Y. Yi et al. [11] investigate the utilization of drones and protective shells for urban air quality monitoring. Lastly, Gómez, C., & Green, D. R. [12] explore the application of drones and protective enclosures for oil and gas pipeline inspection, while J. Li et al. [13] study power line inspection and maintenance using UAVs. ...

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Design of a Shell to Protect Sensors and Drones

... Overall similarity and partial similarity are used for case retrieval to find potential deficits, where the same cases have the max similarity and have been classified perfectly. By applying feature weights we can put special emphasis on some features for the similarity calculation, which can be seen in our former work [7] to improve the system accuracy and efficiency. ...

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A Fault Diagnosis System Based on Case Decision Technology for UAV Inspection of Power Lines

... From the view of recognition, CBR involves human thinking in an integrated sense, logics and creativity, and can avoid abstract knowledge insufficient within the field of the traditional Rule-based reasoning (RBR) which is just a simple simulation of abstract thinking [3]. Case intelligent system can use the past experience of success and failures to guide problem-solving, assist user in refining the details, access the knowledge and experience in the case library, so the case decision system proposed for fault diagnosis can help user finding potential problem in automatic line-inspection, and use more imaginative thinking in decision-making really. ...

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A Fault Diagnosis System Based on Case Decision Technology for UAV Inspection of Power Lines

... The former cases can also be used to evaluate the new issues and new programs of problem-solving [9], and prevent the potential errors in the future. Cases can be reused by similarity computing as case knowledge space conversion, which is the glorious with exciting highlight in the construction of CBR intelligent system, and the characteristic advantage distinguishes CBR systems from RBR systems thoroughly [10]. ...

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Case-Intelligence Recommendation on Massive Contents Processing through Dynamic Computing

... Experimental results are shown in table 2, with the weights of each impact factors computed. As the most important process in CBR cycle, case retrieval is the key and RBF retrieval model can be seen in [9] also with the weights of each attribute are computed for case selection. Those results suggest our synthesis reasoning can combine various reasoning principles and integrate many ML methods useful to enlarge the system's ability. ...

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URT train energy-saving scheme optimized on case intelligence using SRS and RBF