Memory and forgetting: An improved dynamic maintenance method for case-based reasoning

Yan, Aijun; Li, Qian; Zhang, Chunxiao

doi:10.1016/j.ins.2014.07.040

Cited by 15 publications

(7 citation statements)

References 23 publications

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“…Taking the case solution as the electrode current setting value of the furnace condition, after case reuse, the new case needs to be evaluated 12 in order to make the necessary case storage. The specific operation is as follows.…”

Section: An Intelligent Optimization Control Methods For Electrode Curmentioning

confidence: 99%

An intelligent optimization control method for the electrode current of submerged arc furnaces based on case reasoning

Chang

Zhu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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Due to the nonlinearity, strong coupling, and time-varying characteristics of three-phase electrode lift system of submerged arc furnace, the existing manual operation has the problems of electrode control hysteresis, poor balance of three-phase electrode current, and blindness of electrode current target setting. An intelligent optimization control method for the electrode current of submerged arc furnace based on case reasoning is proposed in this article, which is used to realize the automatic control of the electrode control system of the submerged arc furnace. First, the optimization model of electrode current setting value of the submerged arc furnace is established by the case-based reasoning method, and the corresponding electrode current value is calculated to maximize the yield in the safe power range of the furnace. Next, a three-phase electrode current decoupling controller is designed based on fuzzy rules. Finally, an intelligent optimization control system of three-phase electrode current of submerged arc furnace is designed and its superiority is verified by comparison with the proportional–integral–derivative controller. The designed control system has been applied to the smelting production of submerged arc furnace in a domestic smelter. The simulation and industrial operation results show that the system realizes automatic balance adjustment of electrode current of submerged arc furnace under normal working conditions, which greatly reduces the labor intensity of the operator, increases the smelting yield, reduces the unit energy consumption, and brings significant economic and social benefits to the enterprise.

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Section: An Intelligent Optimization Control Methods For Electrode Curmentioning

confidence: 99%

An intelligent optimization control method for the electrode current of submerged arc furnaces based on case reasoning

Chang

Zhu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…The similar and dissimilar associations of this learned case are added at the end of the association table. The addition of new cases certainly ensures the possibility of retrieving cases that are similar to the target problems, however, this continuous addition also enlarges the size of the case base, leading to the complexity and low efficiency of case retrieval tasks [48]. As a consequence, if the new case is extremely similar to a certain past case in the case base, its retention should be dropped for avoiding redundancy.…”

Section: Case Base Maintenancementioning

confidence: 99%

An Efficient Case Retrieval Algorithm for Agricultural Case-Based Reasoning Systems, with Consideration of Case Base Maintenance

et al. 2020

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Case-based reasoning has considerable potential to model decision support systems for smart agriculture, assisting farmers in managing farming operations. However, with the explosive amount of sensing data, these systems may achieve poor performance in knowledge management like case retrieval and case base maintenance. Typical approaches of case retrieval have to traverse all past cases for matching similar ones, leading to low efficiency. Thus, a new case retrieval algorithm for agricultural case-based reasoning systems is proposed in this paper. At the initial stage, an association table is constructed, containing the relationships between all past cases. Afterwards, attributes of a new case are compared with an entry case. According to the similarity measurement, associated similar or dissimilar cases are then compared preferentially, instead of traversing the whole case base. The association of the new case is generated through case retrieval and added in the association table at the step of case retention. The association table is also updated when a closer relationship is detected. The experiment result demonstrates that our proposal enables rapid case retrieval with promising accuracy by comparing a fewer number of past cases. Thus, the retrieval efficiency of our proposal outperforms typical approaches.

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“…Case-based reasoning (CBR) is a highly intelligent technique for problem-solving using old similar experiences to address new problems. The technique suggests that current problems can be assessed by finding previous cases relevant to the current problem, and leverage that case to inform a solution, and update the memory as one learns from the experience (Aamodt and Plaza, 1996;Yan et al, 2014). CBR has been widely and successfully used in various fields such as medicine (Henriet et al, 2014;Bixby, 2013), knowledge-based system (Lupiani et al, 2014) and information seeking behavioral studies (He et al, 2008;Belkin et al, 1995).…”

Section: Introductionmentioning

confidence: 99%

Improving retrieval relevance using users’ explicit feedback

Balakrishnan

Ahmadi

Ravana

2015

Aslib Journal of Information Management

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Purpose – The purpose of this paper is to improve users’ search results relevancy by manipulating their explicit feedback. Design/methodology/approach – CoRRe – an explicit feedback model integrating three popular feedback, namely, Comment-Rating-Referral is proposed in this study. The model is further enhanced using case-based reasoning in retrieving the top-5 results. A search engine prototype was developed using Text REtrieval Conference as the document collection, and results were evaluated at three levels (i.e. top-5, 10 and 15). A user evaluation involving 28 students was administered, focussing on 20 queries. Findings – Both Mean Average Precision and Normalized Discounted Cumulative Gain results indicate CoRRe to have the highest retrieval precisions at all the three levels compared to the other feedback models. Furthermore, independent t-tests showed the precision differences to be significant. Rating was found to be the most popular technique among the participants, producing the best precision compared to referral and comments. Research limitations/implications – The findings suggest that search retrieval relevance can be significantly improved when users’ explicit feedback are integrated, therefore web-based systems should find ways to manipulate users’ feedback to provide better recommendations or search results to the users. Originality/value – The study is novel in the sense that users’ comment, rating and referral were taken into consideration to improve their overall search experience.

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Memory and forgetting: An improved dynamic maintenance method for case-based reasoning

Cited by 15 publications

References 23 publications

An intelligent optimization control method for the electrode current of submerged arc furnaces based on case reasoning

An intelligent optimization control method for the electrode current of submerged arc furnaces based on case reasoning

An Efficient Case Retrieval Algorithm for Agricultural Case-Based Reasoning Systems, with Consideration of Case Base Maintenance

Improving retrieval relevance using users’ explicit feedback

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