Combination Case-Based Reasoning and Clustering Method for Similarity Analysis of Production Manufacturing Process

2015 ◽  
Author(s):  
Sihai Guo ◽  
Fan Yang ◽  
Qibing Lu ◽  
Xingxing Liu
Keyword(s):  
Manufacturing Process ◽  
Similarity Analysis ◽  
Case Based Reasoning ◽  
Clustering Method ◽  
Case Based

scholarly journals An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Mohammed M. Mabkhot ◽  
Ali M. Al-Samhan ◽  
Lotfi Hidri
Keyword(s):  
Decision Support ◽  
Support System ◽  
Manufacturing Process ◽  
Manufacturing Processes ◽  
Case Based Reasoning ◽  
Process Selection ◽  
Product Features ◽  
Material Characteristics ◽  
Manufacturing Process Selection ◽  
Case Based

In nowadays industry 4.0 and changeable manufacturing context, designers and manufacturing engineers struggle to determine appropriate quick, accurate (with flawless quality), and cost-effective processes to design highly customized products to meet customer requirements. To determine manufacturing processes, the matching between product features, material characteristics, and process capabilities needs to be optimized. Finding such an optimized matching is usually referred to as manufacturing process selection (MPS), which is not an easy task because of the infinite combinations of product features, numerous material characteristics, and various manufacturing processes. Although problems associated with MPS have received considerable attention, semantic web technologies are still underexplored and their potential is still uncovered. Almost no previous study has considered combining case-based reasoning (CBR) with ontologies, a famous and powerful semantic web enabler, to achieve MPS. In this study, we developed a decision support system (DSS) for MPS based on ontology-enabled CBR. By applying automatic reasoning and similarity retrieving on an industrial case study, we show that ontologies enable process selection by determining competitive matching between product features, material characteristics, and process capabilities and by endorsing effective case retrieval.

Solving the Message Classification Problem in Voice Interaction Systems

Vestnik MEI ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. 132-139
Author(s):  
Ivan E. Kurilenko ◽  
◽  
Igor E. Nikonov ◽  
Keyword(s):  
Artificial Intelligence ◽  
Classification Problem ◽  
Subject Area ◽  
Text Messages ◽  
Case Based Reasoning ◽  
Short Text ◽  
Proposed Modification ◽  
Voice Interaction ◽  
Text Content ◽  
Case Based

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.

Feature level intentions based product recommendations with case-based reasoning

2018 ◽  
Vol 6 (1) ◽  
pp. 266-274
Author(s):  
D. Teja Santosh ◽  
◽  
K.C. Ravi Kumar ◽  
P. Chiranjeevi ◽  
◽  
...  
Keyword(s):  
Case Based Reasoning ◽  
Product Recommendations ◽  
Case Based

SISTEM PAKAR UNTUK DIAGNOSA PENYAKIT ANAK DENGAN METODE CASE-BASED REASONING DENGAN ALGORITMA SIMILARITY JACCARD PADA PUSKESMAS HALMAHERA SEMARANG

2020 ◽  
Vol 11 (2) ◽  
pp. 57-63
Author(s):  
Didik Trisulo ◽  
Setyawan Wibisono
Keyword(s):  
Case Based Reasoning ◽  
Case Based

Kesehatan merupakan hal yang paling berharga bagi manusia, karena siapa saja rentan mengalami gangguan kesehatan. Anak sangat rentan terhadap kuman penyakit dan kepekaan terhadap gejala suatu penyakit merupakan ketakutan sendiri bagi orang tua. Orang tua merupakan orang awam terhadap dunia kesehatan. Sehingga dalam hal ini di bidang kesehatan lebih membutuhkan seorang pakar yang bisa memudahkan mendiagnosa suatu penyakit lebih cepat agar orang tua dapat melakukan pencegahan lebih awal yang sekiranya bisa membutuhkan waktu lebih lama jika berkonsultasi dengan dokter ahli. Tujuan dari penelitian ini adalah merancang dan sistem pakar untuk diagnosa penyakit anak dengan metode cased-based reasoning dengan algoritma similarity jaccard pada Puskesmas Halmahera Semarang sehingga membantu memberikan informasi tentang diagnosa penyakit anak pada Puskesmas Halmahera Semarang berbasis web.         Perancangan sistem pakar untuk diagnosa penyakit anak dengan metode cased-based reasoning dengan algoritma similarity jaccard pada Puskesmas Halmahera Semarang ini dibuat dengan menggunakan tools seperti PHP, Xampp, Bootstrap.                 Hasil sistem pakar untuk diagnosa penyakit anak dengan metode cased-based reasoning dengan algoritma similarity jaccard pada Puskesmas Halmahera Semarang dapat membantu memberikan informasi tentang diagnosa penyakit anak pada Puskesmas Halmahera Semarang  

Sign in / Sign up

Export Citation Format

Share Document