Article
Mathematics
Huirong Zhang, Zhenyu Zhang, Lixin Zhou, Shuangsheng Wu
Summary: The article discusses how judgment debtors in China try to resist law enforcement by concealing and transferring their property, and proposes a case-based reasoning method for analyzing hidden property. The results show that this method can reduce the work pressure of law enforcement officers and improve the efficiency of handling enforcement cases.
Article
Chemistry, Multidisciplinary
Mengqi Chen, Jingyang Xia, Ruoyun Huang, Weiguo Fang
Summary: Case retrieval is a critical process in case-based reasoning, and its quality relies on case similarity measures. This study proposes an improved case retrieval method for aeroengine fault diagnosis by incorporating attitudinal Choquet integral and 2-order additive measure to consider attribute interactions and decision makers' attitudes. The enhanced method integrates local similarity, attribute importance, attribute interactions, and decision makers' attitudes, leading to more comprehensive and reasonable global similarity and high-quality recommendations.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Hardware & Architecture
Simon Pichette, Claude Thibeault
Summary: Due to commercial pressures, North-American printed circuit-board assembly manufacturers have had to reposition themselves in the more difficult market segment of HMLV products. We propose a hybrid approach based on knowledge modeling and case-based reasoning for automated diagnosis of assembled printed circuit boards. Our diagnostic system shows a higher success rate than the reference commercial tool and utilizes case base data to provide repair suggestions.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
(2023)
Article
Business
Ting Luo, Jing Zhou, Shang Gao
Summary: Crowdfunding has become an important financing channel for startups. This study proposes an integrated model of text analytics and case-based reasoning to assist in experience mining when designing crowdfunding projects. The model utilizes text analytics methods to extract features and adopts local similarity measures for case retrieval. The effectiveness of the model is verified using project data on the Kickstarter platform, demonstrating its value in improving design schemes and financing performance for fundraisers.
ELECTRONIC COMMERCE RESEARCH
(2023)
Article
Construction & Building Technology
Kaicheng Shen, Yimin Zhu, Jianchao Pan, Xiaodong Li
Summary: Precast components are crucial in prefabricated construction. Joint design plays a vital role in structural stability, but has been underutilizing tacit knowledge. This study proposes a case-based reasoning model to improve joint design efficiency based on tacit knowledge. Results show that the model is highly accurate and effective, especially for different buildings.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2023)
Article
Engineering, Environmental
Feiyue Liu, Zhenqi Yang, Wenxue Deng, Tianhong Yang, Jingren Zhou, Qinglei Yu, Yachun Mao
Summary: A two-stage monitoring system was designed to manage and prevent rock landslides in open-pit mines, using a case-based reasoning approach to find similar cases for landslide prediction and establishing an early warning system with multiple monitoring data. The system can provide ideas and solutions for early warning of rock landslides in similar open-pit mines based on a case study in Dagushan.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Biology
Bruno Perez, Christophe Lang, Julien Henriet, Laurent Philippe, Frederic Auber
Summary: This paper introduces an architecture that combines a Multi-Agent System with Case-Based Reasoning to manage risks in an operating room during surgical procedures. By simulating various situations and analyzing data, the system can determine alert thresholds that are not predefined and shows that the proposed thresholds are more efficient.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Mathematics
Tingting Zhao, Jie Lin, Zhenyu Zhang
Summary: This paper explores a new method for predicting posting popularity in online communities using a case-based reasoning approach combined with attribute feature mining, with the concept of intrinsically interpretable attribute features proposed. The study shows that this method is suitable for the complex social network environment and can effectively support decision makers in finding excellent solutions for popularity prediction in the network community.
Article
Engineering, Civil
Feng Yu, Bo Fan, Chuanshen Qin, Chen Yao
Summary: This paper proposes a case-based reasoning (CBR) approach to support fault-control decision-making in disaster response. By analyzing historical cases and reconstructing a scenario model, relevant knowledge is acquired and target fault-control measures are generated. The results show that this approach is an effective way to provide fault-control suggestions.
NATURAL HAZARDS REVIEW
(2023)
Article
Economics
Liguo Fei, Yanqing Wang
Summary: This paper investigates methods of predicting emergency materials demand using case-based reasoning (CBR) and the Dempster-Shafer theory. It proposes an improved case retrieval strategy and a scenario-matching method for natural hazards, as well as a dynamic prediction model. The effectiveness of the proposed methods is demonstrated through empirical analysis using typhoon and earthquake disasters as case studies.
SOCIO-ECONOMIC PLANNING SCIENCES
(2022)
Article
Construction & Building Technology
Mingxiao Li, Guangbin Wang, Dongping Cao, Jide Sun, Guangshe Jia
Summary: Accurately estimating construction duration and setting reasonable project schedule goals are crucial in airport projects due to their substantial economic and social benefits. However, the uncertainties and complexities associated with terminal construction projects limit the usability of traditional estimation methods. Case-based reasoning (CBR) has been employed to estimate construction duration in the early project stage, but the detailed procedures require further investigation to enhance its performance.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Yousra Asim, Ahmad Kamran Malik, Basit Raza, Ahmad R. Shahid, Nafees Qamar
Summary: Influential bloggers have the ability to understand and influence mass psychology, which can be beneficial for corporations looking to disseminate products or services quickly and effectively. This paper proposes a Framework for Influential Blogger Prediction using Case-Based Reasoning, which outperforms existing techniques in predicting and classifying influential bloggers. The CBR approach is found to optimize baseline techniques for better influential blogger identification.
Article
Computer Science, Information Systems
Shaima Hameed, Yousef Elsheikh, Mohammad Azzeh
Summary: Software development companies have faced long-standing challenges in accurately estimating the effort required for software projects. However, research has shown that machine learning techniques, such as case-based reasoning, can improve accuracy. The case-based reasoning technique, though effective, has difficulty in tuning its multiple parameters. This paper proposes the use of a genetic algorithm to find the best combination of parameters and improve accuracy. The results show the effectiveness of this approach, which is beneficial for project managers in financial planning and cost control.
INFORMATION AND SOFTWARE TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Xiaoqian Liu, Yingjun Zhang, Jingping Wang, Hua Huang, Hui Yin
Summary: In this study, a multi-source and multivariate ozone prediction model based on fuzzy cognitive maps (FCMs) and evidential reasoning theory, called ERC-FCM, is proposed. The model addresses the challenges of complex evolution trend of ozone, cross-interference phenomena, and low-quality monitoring data. Experimental results demonstrate the superiority of ERC-FCM in terms of prediction accuracy compared to other classical FCM-based methods.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Chemical
Jingwei Zeng, Guoxun Jing, Qifeng Zhu, Hao Sun
Summary: This paper presents a method for generating an emergency response plan for spontaneous combustion based on case-based reasoning. By establishing a case library, applying CBR technology, and utilizing a Python program, an emergency response plan for spontaneous combustion can be quickly generated. The results show that the proposed method is consistent with the actual situation and more accurate compared to other algorithms, providing support for emergency response plan generation in spontaneous combustion incidents.
