A new personalization approach by case-based reasoning and fuzzy logic

2014 ◽  
Author(s):  
Wafa Mahdi ◽  
Makram Soui ◽  
Mourad Abed
Keyword(s):  
Fuzzy Logic ◽  
Case Based Reasoning ◽  
Case Based

Soft case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 267-269 ◽  
Author(s):  
WILLIAM CHEETHAM ◽  
SIMON SHIU ◽  
ROSINA O. WEBER
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Network Theory ◽  
Probabilistic Reasoning ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Soft Computing Techniques ◽  
Neural Network Theory ◽  
Case Based

The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

A Cotton Disease Diagnosis Method Using a Combined Algorithm of Case-Based Reasoning and Fuzzy Logic

2020 ◽  
Author(s):  
Yuhong Dong ◽  
Zetian Fu ◽  
Stevan Stankovski ◽  
Yaoqi Peng ◽  
Xinxing Li
Keyword(s):  
Fuzzy Logic ◽  
Disease Diagnosis ◽  
Case Based Reasoning ◽  
Cotton Production ◽  
Scoring Method ◽  
Disease Symptoms ◽  
Diagnosis Method ◽  
And Control ◽  
Combined Algorithm ◽  
Case Based

Abstract In this study, a cotton disease diagnosis method that uses a combined algorithm of case-based reasoning (CBR) and fuzzy logic was designed and implemented. It focuses on the prevention, diagnosis and control of diseases affecting cotton production in China. Conventional methods of disease diagnosis are primarily based on CBR with reference to user-provided symptoms; however, in most cases, user-provided symptoms do not fully meet the requirements of CBR. To address this problem, fuzzy logic is incorporated into CBR to allow for more flexible and accurate models. With the help of CBR and fuzzy reasoning, three diagnostic results can be obtained by the cotton disease diagnosis system (CDDS) constructed in this study: success, success but not exact and failure. To verify the reliability of the CDDS and its ability to diagnose cotton diseases, its diagnostic accuracy and stability were analyzed and compared with the results obtained by the traditional expert scoring method. The analysis results reveal that the CDDS can achieve a high diagnostic success rate (above 90%) and better diagnostic stability than the traditional expert scoring method when at least four disease symptoms are input. The CDDS provides an independent and objective source of information to assist farmers in the diagnosis and prevention of cotton diseases.

Achieving quality assurance functionality in the food industry using a hybrid case-based reasoning and fuzzy logic approach

2012 ◽  
Vol 39 (5) ◽  
pp. 5251-5261 ◽  
Author(s):  
S.I. Lao ◽  
K.L. Choy ◽  
G.T.S. Ho ◽  
Richard C.M. Yam ◽  
Y.C. Tsim ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Quality Assurance ◽  
Food Industry ◽  
Case Based Reasoning ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Case Based

scholarly journals Case-Based Reasoning in Web Break Sensitivity Evaluation in a Paper Machine

2005 ◽  
Vol 9 (5) ◽  
pp. 556-561 ◽  
Author(s):  
Timo Ahola ◽  
◽  
Kauko Leiviskä
Keyword(s):  
Fuzzy Logic ◽  
Case Based Reasoning ◽  
Paper Machine ◽  
New Approach ◽  
Mill Scale ◽  
Paper Machines ◽  
Sensitivity Evaluation ◽  
Good Possibility ◽  
Case Based

This paper proposes a new approach for monitoring the the paper web break tendency in modern paper machines. The approach combines linguistic equations and fuzzy logic in a case-based reasoning framework. The development is based on actual mill data and simulations, and early prototyping is used to validate the approach in practice. The system has been tested on two Finnish paper machines with encouraging results showing good possibility for actual mill-scale application.

Sign in / Sign up

Export Citation Format

Share Document