scholarly journals PERFORMING THE RETRIEVE STEP IN A CASE-BASED REASONING SYSTEM FOR DECISION MAKING IN INTRUSION SCENARIOS

2009 ◽  
Author(s):  
Jesus Conesa ◽  
Angela Ribeiro
Keyword(s):  
Decision Making ◽  
Case Based Reasoning ◽  
Reasoning System ◽  
Case Based

scholarly journals A Case-Based Reasoning System for Aiding Physicians in Decision Making

2020 ◽  
Vol 12 (02) ◽  
pp. 63-74
Author(s):  
Venkata A. Paruchuri ◽  
Bobby C. Granville
Keyword(s):  
Decision Making ◽  
Case Based Reasoning ◽  
Reasoning System ◽  
Case Based

scholarly journals Using extended siamese networks to provide decision support in aquaculture operations

2021 ◽  
Author(s):  
Bjørn Magnus Mathisen ◽  
Kerstin Bach ◽  
Agnar Aamodt
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Similar Case ◽  
Decision Makers ◽  
Similarity Function ◽  
Case Based Reasoning ◽  
Similarity Learning ◽  
Reasoning System ◽  
Siamese Networks ◽  
Case Based

AbstractAquaculture as an industry is quickly expanding. As a result, new aquaculture sites are being established at more exposed locations previously deemed unfit because they are more difficult and resource demanding to safely operate than are traditional sites. To help the industry deal with these challenges, we have developed a decision support system to support decision makers in establishing better plans and make decisions that facilitate operating these sites in an optimal manner. We propose a case-based reasoning system called aquaculture case-based reasoning (AQCBR), which is able to predict the success of an aquaculture operation at a specific site, based on previously applied and recorded cases. In particular, AQCBR is trained to learn a similarity function between recorded operational situations/cases and use the most similar case to provide explanation-by-example information for its predictions. The novelty of AQCBR is that it uses extended Siamese neural networks to learn the similarity between cases. Our extensive experimental evaluation shows that extended Siamese neural networks outperform state-of-the-art methods for similarity learning in this task, demonstrating the effectiveness and the feasibility of our approach.

A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy

2011 ◽  
Vol 38 (12) ◽  
pp. 6528-6538 ◽  
Author(s):  
Nishikant Mishra ◽  
Sanja Petrovic ◽  
Santhanam Sundar
Keyword(s):  
Prostate Cancer ◽  
Case Based Reasoning ◽  
Cancer Radiotherapy ◽  
Reasoning System ◽  
Dose Planning ◽  
Prostate Cancer Radiotherapy ◽  
Case Based ◽  
Self Adaptive

A Case Based Reasoning System For Recommendation Of Restaurant In Jimbaran Using K-Nearest Neighbor

2020 ◽  
Vol 9 (2) ◽  
pp. 267
Author(s):  
I Gede Teguh Mahardika ◽  
I Wayan Supriana
Keyword(s):  
Recommendation System ◽  
Nearest Neighbor ◽  
Case Based Reasoning ◽  
Retrieval Process ◽  
K Nearest Neighbor ◽  
Reasoning System ◽  
Human Ability ◽  
And Function ◽  
Case Based ◽  
Selection Of

Culinary is one of the favorite businesses today. The number of considerations to choose a restaurant or place to visit becomes one of the factors that is difficult to determine the restaurant or place to eat. To get the desired place to eat advice, one needs a recommendation system. Decisions made by the recommendation system can be used as a reference to determine the choice of restaurants. One method that can be used to build a recommendation system is Case Based Reasoning. The Case Based Reasoning (CBR) method mimics human ability to solve a problem or cases. The retrieval process is the most important stage, because at this stage the search for a solution for a new case is carried out. The study used the K-Nearest Neighbor method to find closeness between new cases and case bases. With the selection of features used as domains in the system, the results of recommendations presented can be more suggestive and accurate. The system successfully provides complex recommendations based on the type and type of food entered by the user. Based on blackbox testing, the system has features that can be used and function properly according to the purpose of creating the system.

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