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

Zhai, Zhaoyu; Ortega, José Fernán Martínez; Martínez, Néstor Lucas; Xu, Hao

doi:10.3390/agriculture10090387

Cited by 5 publications

(3 citation statements)

References 45 publications

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“…The key components of case‐based reasoning are the similar history, case retrieval, and case correction (Zhai et al., 2020). First, rice growth period, rice variety, organic matter (OM), alkali‐hydrolyzable nitrogen (AN), available phosphorus (AP), available potassium (AK), pH, and yield were used as case feature attributes (Ge et al., 2023).…”

Section: Reasoning Methods For Rice Fertilization Strategies Based On...mentioning

confidence: 99%

A reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph

Lin,

Li,

Peng

et al. 2024

Transactions in GIS

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The lack of multidimensional knowledge means that current reasoning methods for rice fertilization cannot make decisions accurate when faced with complex spatiotemporal conditions in general. Therefore, we propose a reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph. First, we systematically organize multisource expert knowledge about rice fertilization, and construct an ontology for rice fertilization consisting of five core elements: rice variety, planting environment, nutrition diagnosis, fertilization schemes, and time and place. Spatiotemporal differences in rice fertilization knowledge are expressed by assessing spatiotemporal concepts, relations, and state instances. Second, we propose a reasoning method for rice fertilization strategy based on the constructed knowledge graph. This method leverages a certainty factor model for nutrition diagnosis and integrates case‐based and rule‐based reasoning to determine fertilization schemes for different stages. Finally, taking Pucheng County, China, as an example, knowledge from crowd‐sensing data is obtained to construct a knowledge graph using the proposed method. The results demonstrate the method can support the expression and complex reasoning of rice fertilization decisions under different spatiotemporal conditions.

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Section: Reasoning Methods For Rice Fertilization Strategies Based On...mentioning

confidence: 99%

A reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph

Lin,

Li,

Peng

et al. 2024

Transactions in GIS

View full text Add to dashboard Cite

show abstract

“…Effective retrieval is not only to find similar cases but also to find useful similar cases. To date, many mature retrieval methods have been formed, including the nearest neighbor algorithm (NN) (Kang et al 2010), knowledge-guided approach (Rallabandi and Sett 2008), template retrieval (Sharifi et al 2013), two-level retrieval (Wang et al 2019), and index-based retrieval (Zhai et al 2020), etc. The efficiency of these retrieval methods depends to a large extent on the following.…”

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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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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“…In general, there are 4 stages of problem-solving based on case-based reasoning that is used in problem-solving, namely retrieve, reuse, revise, and retain [9]. The problem-solving stage has an important role, which is if you cannot retrieve a case that is similar to the previous case, the CBR stage cannot be continued [10]. The solution is in the form of a cycle as shown in Figure 1, CBR Stages.…”

Section: Case Base Reasoningmentioning

confidence: 99%

Case Based Reasoning using K-Nearest Neighbor with Euclidean Distance for Early Diagnosis of Personality Disorder

Jones

Hardiyanti

2021

IJISTECH

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A personality disorder is a condition of a person with an extreme personality that causes the sufferer to have unhealthy and different thoughts patterns and behavior from other people. The personality disorders discussed in this study consisted of 110 diseases with 300 case data and 68 symptoms. Based on Basic Health Research (Riskesdas) 2018 data, it shows that more than 19 million people aged 15 years and over were affected by mental-emotional disorders. Data from the Statistics Indonesia in 2019 that the population of Indonesia is around 265 million people, while according to the Indonesian Clinical Psychologist Association, the number of verified professional psychologists is 1,599 clinical psychologists out of a total membership of 2,078 as of January 2019. However, this figure does not meet the standards of the World Health Organization (WHO), which is that psychologists serve 30 thousand people. This shows that Indonesia still lacks around 28,970 psychologists. The unequal distribution of professional psychologists has made psychologists need a long time to provide a diagnosis because of the number of patients being inversely proportional to the availability of psychologists in Indonesia. Moreover, there is not enough patient knowledge about the symptoms they feel. This study aims to produce a system for diagnosing personality disorders. This study is a case based reasoning to solve problems that have occurred in previous cases using K-Nearest Neighbor to classify data based on the closest distance using the calculation of the Euclidean Distance. Algorithm testing for the system used the Confusion Matrix test. Based on the results of testing data in the 60 case data using K-nearest Neighbor and the calculation of the Euclidean Distance with a score of K=3, it is known that 60 data have 100% similarity to cases with a personality disorder. Meanwhile, testing new cases with 10 case data that were not in the knowledge base was also conducted showing that 9 cases had 100% similarity to the previous case, while another case had 90% similarity to the previous case.

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

Cited by 5 publications

References 45 publications

A reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph

A reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph

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

Case Based Reasoning using K-Nearest Neighbor with Euclidean Distance for Early Diagnosis of Personality Disorder

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