scholarly journals Implementasi Metode Case Based Reasoning Untuk Mendeteksi Kerusakan Televisi

2021 ◽  
Vol 5 (2) ◽  
pp. 624
Author(s):  
Sursih Wulandari ◽  
Marnis Nasution ◽  
Mustafa Haris Munandar
Keyword(s):  
High Weight ◽  
Study Data ◽  
Design System ◽  
Case Based Reasoning ◽  
Collection System ◽  
Literature Study ◽  
Knowledge Based ◽  
Testing Case ◽  
Case Based ◽  
System Program

The process of deteriorating television should indeed be done by an expert who is a television expert himself, but because television is a tool that is no longer common for people to know him, many people also have television in their respective homes. Even for television repairs, it is quite expensive, so some people who have televisions can do television maintenance at home. The lack of knowledge possessed by the community can lead to wrong handling of television maintenance / maintenance and this has a fatal impact. Hopefully the existence of this system can help the community in diagnosing the damage to their televisions. In that case they need not bother to call for repairmen or bring in a television repair shop. Here the authors provide solutions to solve the problems that often arise on television. In this study, it discusses how to care for television officers. The research objective is to analyze a desktop-based expert system program that contains the knowledge of an expert / doctor whose truth is believed to have the ability to be able to diagnose the disease from the symptoms of damage that has been damaged by television damage quickly and precisely. The stages of research carried out in this study include literature study, data collection, system design, system creation, system testing. Case Based Reasoning is a method used to build a knowledge-based system. The source of system knowledge is obtained by collecting the handling of cases by an expert / expert. Therefore, many problems in television damage are usually due to the negligence of the television owner himself. The first step in solving a problem is by first identifying the scope of the problem to be resolved, this also applies to any Artificial Intelligence (AI) programming. The results obtained in the study for the diagnosis of conjunctivitis were the value of old cases and new cases which obtained a high weight value, namely 1 from the third case

scholarly journals Application of the Case Based Learning (CBR) Method to Diagnose Conjunctivitis

SinkrOn ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 176-182
Author(s):  
Marco Ramadhani ◽  
Volvo Sihombing ◽  
Gomal Juni Yanris
Keyword(s):  
Expert System ◽  
Expert Knowledge ◽  
Study Data ◽  
Eye Diseases ◽  
Design System ◽  
Case Based Reasoning ◽  
Literature Study ◽  
Case Based Learning ◽  
Micro Organisms ◽  
Case Based

Conjunctivitis is an inflammation of the conjunctiva or the outer layer of the eye and the inner lining of the eyelids caused by micro-organisms or viruses, bacteria, fungi, chlamydia, allergies, irritation of chemicals. The problems that arise start from common symptoms that are often shown or are shown by eye diseases such as redness of the eye area and then cause pain and soreness. Diagnosis can be made by an ophthalmologist. In addition, to diagnose eye diseases, an expert system can also be used to pour expert knowledge into an expert system, thus helping diagnose eye diseases. The research objective is to analyze a desktop-based expert system program that contains the knowledge of a trusted expert/doctor who has the ability to be able to diagnose the disease from the eye disease symptoms felt by the patient quickly and precisely. The stages of research carried out in this study include literature study, data collection, system design, system creation, system testing. In addition, the authors developed using the Case-Based Reasoning (CBR) method, which is one method of building an expert system by making decisions from cases with the solution of previous cases to determine the type of conjunctivitis.

Applying design-dependent knowledge in structural engineering design

1989 ◽  
Vol 3 (2) ◽  
pp. 111-123 ◽  
Author(s):  
H. Craig Howard ◽  
Jenmu Wang ◽  
Francois Daube ◽  
Taufiq Rafiq
Keyword(s):  
Engineering Design ◽  
Structural Engineering ◽  
Digital Data ◽  
Long Term Results ◽  
Design System ◽  
Case Based Reasoning ◽  
Knowledge Based ◽  
Component Design ◽  
Structural Engineers ◽  
Case Based

Recent knowledge-based expert systems for structural engineering design have focused on design-independent knowledge (abstract reasoning rules for designing), and while great strides have been made in that area, there is still a significant need to develop systems to take advantage of the wealth of knowledge contained in every substantial structural design. On the other hand, previous database-oriented design efforts have focused primarily on knowledge-poor databases of solutions, in which the traditional engineering handbook of solutions has simply been replaced by digital data. The challenge is to find a way to capture and apply the kind of case-based, design-dependent knowledge that structural engineers have traditionally used. The long-term results will be better structural designs and better structural designers. This paper discusses the character of the design-dependent knowledge in a structural engineering context, describes two initial applications of case-based reasoning to component design, and presents a general paradigm for a knowledge-based design system integrating rule-based and case-based reasoning.

The Study of Hybrid Gaussian CBR Technique and Using in Camshaft Design System

2010 ◽  
Vol 108-111 ◽  
pp. 603-607
Author(s):  
Wei Yan ◽  
Xue Qing Li ◽  
Xu Guang Tan ◽  
De Hui Tong ◽  
Qi Gao
Keyword(s):  
Expert System ◽  
Decision Model ◽  
Nearest Neighbor ◽  
Design System ◽  
Case Based Reasoning ◽  
K Nearest Neighbor ◽  
Engine Design ◽  
Cam Profile ◽  
Aided Design ◽  
Case Based

In this paper, we propose a hybrid decision model using case-based reasoning augmented the Gaussian and k nearest neighbor methods for aided design camshaft in engine. The hybrid Gaussian k-NN (HGKNN) CBR scheme is designed to compute memberships between cam profile and engine parameters, which provides a more flexible and practical mechanism for reusing the decision knowledge. These methods were implemented in the database application and expert system following the examples of Cam Profile. To get the designed case, the retrieved results were compared and analyzed by HGKNN and k-NN algorithm in the CBR database. It proves the validity of HGKNN and CBR design system is used successfully in engine design process.

scholarly journals Knowledge Service Technology for Supporting Intelligent Product Design

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haiqiao Wang ◽  
Ruikun Niu
Keyword(s):  
Decision Making ◽  
Intelligent Design ◽  
Measurement Method ◽  
Numerical Control ◽  
Similarity Measurement ◽  
Case Based Reasoning ◽  
Knowledge Service ◽  
Knowledge Based ◽  
Weight Coefficients ◽  
Case Based

In this paper, a knowledge service method that supports the intelligent design of products is investigated. The proposed method provides the solutions to computational problems and reasoning and decision-making problems in the field of intelligent design. The requirement analysis of a knowledge-based intelligent design system integrates design knowledge into case-based reasoning activities through scheme analysis, scheme evaluation, and scheme adjustment, thus achieving knowledge-based intelligent reasoning and decision-making. During the similarity matching, a new hybrid similarity measurement method is proposed to calculate the similarity of crisp and fuzzy sets. This method integrates the fuzzy set similarity theory based on the traditional similarity measurement method. A method of attribute level classification is proposed to assign weight coefficients. The attributes are divided into the primary matching and auxiliary matching levels according to the decisiveness of case matching, and the set of weight coefficients is continuously and dynamically updated through case-based reasoning learning. Then, the weighted global similarity measure is used to obtain the set of similar cases from the case database. Finally, a design example of a computer numerical control tool holder product is studied to present the practicability and effectiveness of the proposed method.

Towards a case-based computational model for the creative design of electromagnetic devices

2011 ◽  
Vol 60 (4) ◽  
pp. 485-496
Author(s):  
Jun Ouyang ◽  
David Lowther
Keyword(s):  
Computational Model ◽  
Feature Space ◽  
Practical Significance ◽  
Design System ◽  
Case Based Reasoning ◽  
Creative Design ◽  
Electromagnetic Devices ◽  
Soft Computing Techniques ◽  
Case Base ◽  
Case Based

Towards a case-based computational model for the creative design of electromagnetic devicesIn order to explore creativity in design, a computational model based on Case-Based Reasoning (CBR) (an approach to employing old experiences to solve new problems) and other soft computing techniques from machine learning, is proposed in this paper. The new model is able to address the four challenging issues: generation of a design prototype from incomplete requirements, judgment and improvement of system performance given a sparse initial case base library, extraction of critical features from a given feature space, adaptation of retrieved previous solutions to similar problems for deriving a solution to a given design task. The core principle within this model is that different knowledge from various level cases can be explicitly explored and integrated into a practical design process. In order to demonstrate the practical significance of our presented computational model, a case-based design system for EM devices, which is capable of deriving a new design prototype from a real-world device case base with high dimensionality, has been developed.

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