Developing a new intelligent system for the diagnosis of oral medicine with case‐based reasoning approach

Oral Diseases ◽  
2019 ◽  
Vol 25 (6) ◽  
pp. 1555-1563 ◽  
Author(s):  
Hamideh Ehtesham ◽  
Reza Safdari ◽  
Arash Mansourian ◽  
Shahram Tahmasebian ◽  
Niloofar Mohammadzadeh ◽  
...  
Keyword(s):  
Intelligent System ◽  
Case Based Reasoning ◽  
Oral Medicine ◽  
Case Based

Integrating fuzzy case-based reasoning, parametric and feature-based cost estimation methods for machining process

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fentahun Moges Kasie ◽  
Glen Bright
Keyword(s):  
Cost Estimation ◽  
Intelligent System ◽  
Machining Process ◽  
Estimation Methods ◽  
Case Based Reasoning ◽  
Cost Estimates ◽  
Content Type ◽  
Estimation Techniques ◽  
Feature Based ◽  
Case Based

Purpose This paper aims to propose an intelligent system that serves as a cost estimator when new part orders are received from customers. Design/methodology/approach The methodologies applied in this study were case-based reasoning (CBR), analytic hierarchy process, rule-based reasoning and fuzzy set theory for case retrieval. The retrieved cases were revised using parametric and feature-based cost estimation techniques. Cases were represented using an object-oriented (OO) approach to characterize them in n-dimensional Euclidean vector space. Findings The proposed cost estimator retrieves historical cases that have the most similar cost estimates to the current new orders. Further, it revises the retrieved cost estimates based on attribute differences between new and retrieved cases using parametric and feature-based cost estimation techniques. Research limitations/implications The proposed system was illustrated using a numerical example by considering different lathe machine operations in a computer-based laboratory environment; however, its applicability was not validated in industrial situations. Originality/value Different intelligent methods were proposed in the past; however, the combination of fuzzy CBR, parametric and feature-oriented methods was not addressed in product cost estimation problems.

scholarly journals Sistem Cerdas Permainan Papan The Battle Of Honor dengan Decision Making dan Machine Learning

2021 ◽  
Vol 12 (2) ◽  
pp. 136
Author(s):  
Arnan Dwika Diasmara ◽  
Aditya Wikan Mahastama ◽  
Antonius Rachmat Chrismanto
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Intelligent System ◽  
Third Party ◽  
Case Based Reasoning ◽  
Board Game ◽  
Rule Based ◽  
Case Based ◽  
Rule Based Systems

Abstract. Intelligent System of the Battle of Honor Board Game with Decision Making and Machine Learning. The Battle of Honor is a board game where 2 players face each other to bring down their opponent's flag. This game requires a third party to act as the referee because the players cannot see each other's pawns during the game. The solution to this is to implement Rule-Based Systems (RBS) on a system developed with Unity to support the referee's role in making decisions based on the rules of the game. Researchers also develop Artificial Intelligence (AI) as opposed to applying Case-Based reasoning (CBR). The application of CBR is supported by the nearest neighbor algorithm to find cases that have a high degree of similarity. In the basic test, the results of the CBR test were obtained with the highest formulated accuracy of the 3 examiners, namely 97.101%. In testing the AI scenario as a referee, it is analyzed through colliding pieces and gives the right decision in determining victoryKeywords: The Battle of Honor, CBR, RBS, unity, AIAbstrak. The Battle of Honor merupakan permainan papan dimana 2 pemain saling berhadapan untuk menjatuhkan bendera lawannya. Permainan ini membutuhkan pihak ketiga yang berperan sebagai wasit karena pemain yang saling berhadapan tidak dapat saling melihat bidak lawannya. Solusi dari hal tersebut yaitu mengimplementasikan Rule-Based Systems (RBS) pada sistem yang dikembangkan dengan Unity untuk mendukung peran wasit dalam memberikan keputusan berdasarkan aturan permainan. Peneliti juga mengembangkan Artificial Intelligence (AI) sebagai lawan dengan menerapkan Case-Based reasoning (CBR). Penerapan CBR didukung dengan algoritma nearest neighbour untuk mencari kasus yang memiliki tingkat kemiripan yang tinggi. Pada pengujian dasar didapatkan hasil uji CBR dengan accuracy yang dirumuskan tertinggi dari 3 penguji yaitu 97,101%. Pada pengujian skenario AI sebagai wasit dianalisis lewat bidak yang bertabrakan dan memberikan keputusan yang tepat dalam menentukan kemenangan.Kata Kunci: The Battle of Honor, CBR, RBS, unity, AI

scholarly journals Designing Intelligent Tutoring Systems: A Personalization Strategy using Case-Based Reasoning and Multi-Agent Systems

2013 ◽  
Vol 2 (1) ◽  
pp. 41-54
Author(s):  
Carolina González ◽  
Juan Carlos Burguillo ◽  
Martín Llamas ◽  
Rosalía Laza
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Agents ◽  
Intelligent System ◽  
Intelligent Tutoring ◽  
Educational Systems ◽  
Case Based Reasoning ◽  
Multi Agent Systems ◽  
Tutoring Systems ◽  
Student Profile ◽  
Case Based

Intelligent Tutoring Systems (ITSs) are educational systems that use artificial intelligence techniques for representing the knowledge. ITSs design is often criticized for being a complex and challenging process. In this article, we propose a framework for the ITSs design using Case Based Reasoning (CBR) and Multiagent systems (MAS). The major advantage of using CBR is to allow the intelligent system to propose smart and quick solutions to problems, even in complex domains, avoiding the time necessary to derive those solutions from scratch. The use of intelligent agents and MAS architectures supports the retrieval of similar students models and the adaptation of teaching strategies according to the student profile. We describe deeply how the combination of both technologies helps to simplify the design of new ITSs and personalize the e-learning process for each student

scholarly journals Pembuatan Aplikasi Diagnosa Kerusakan Mesin Sepeda Motor Matic dengan Case-Based Reasoning

2015 ◽  
Vol 2 (3) ◽  
pp. 192
Author(s):  
Sandy Kosasi
Keyword(s):  
Intelligent System ◽  
Automatic Transmission ◽  
Case Based Reasoning ◽  
Test Results ◽  
Design Development ◽  
System Validation ◽  
Wheeled Vehicle ◽  
System Maintenance ◽  
Motorcycle Engine ◽  
Case Based

Sepeda motor matic sebagai terobosan baru kendaraan roda dua dengan transmisi otomatis memberikan implikasi kepada sistem perawatannya. Jumlah mekanik yang terbatas dan minimnya pengetahuan pengguna menyebabkan berbagai kesulitan dalam perawatannya khususnya dalam mengatasi kerusakan mesin. Pembuatan aplikasi sistem cerdas melalui metode case-based reasoning dapat memberikan kemudahan melakukan diagnosis awal secara mandiri. Case-based reasoning memiliki kemampuan dapat memberikan hasil diagnosis yang lebih akurat berdasarkan kejadian terdahulu dan dapat direvisi kembali dalam memecahkan permasalahan terbaru. Metode perancangan aplikasinya menggunakan reuse-based yang meliputi enam tahap yaitu spesifikasi persyaratan, analisis komponen, modifikasi persyaratan, integrasi design sistem dengan reuse, pengembangan dan integrasi, serta validasi sistem. Tujuan penelitian untuk melakukan diagnosa kerusakan mesin sepeda motor matic dan memberikan solusi awal mengenai kondisi kerusakan dan pencegahannya melalui media situs web. Hasil pengujian memperlihatkan aplikasi ini memiliki kemampuan mendiagnosa kerusakan dan memberikan solusi penyelesaian masalah dari pengguna dengan rata-rata nilai similaritas antara 0,62 dan 0,7 dengan nilai keakuratan solusi dari pakar sebesar 80% dan 90%. Automatic motorcycles as a new breakthrough of two-wheeled vehicle with an automatic transmission have implications for the system maintenance. A limited number of mechanics and lack of users’ knowledge cause many difficulties in treatment, especially in dealing with the engine damage. The Design of the intelligent system through case-based reasoning method can provide easiness of initial diagnosis independently. Case-based reasoning has the ability to provide more accurate diagnosis results based on the previous events and may be revised to solve the latest problems. The design of application uses a reuse-based method that includes six stages: requirements specification, component analysis, modification of the terms, integration with reuse system design, development and integration, and system validation. The purpose of the research is for diagnosing automatic motorcycle engine damage and provide an initial solution on its condition and prevention through the medium of the website. The test results demonstrate that this application has the ability to diagnose the damage and provide problem solving solutions to the users with an average of similarity value between 0,62 and 0,7 with an accuracy value of expert solutions for 80% and 90%.

scholarly journals Case-Based Reasoning Using The Nearest Neighbor Method For Detection Of Equipment Damage To PLN Power Plant

2020 ◽  
Vol 14 (4) ◽  
pp. 377
Author(s):  
Riska Amalia Praptiwi ◽  
Nur Rokhman ◽  
Wahyono Wahyono
Keyword(s):  
Power Plant ◽  
Test Data ◽  
Nearest Neighbor ◽  
Intelligent System ◽  
Confusion Matrix ◽  
Threshold Value ◽  
Case Based Reasoning ◽  
Periodic Monitoring ◽  
Total Data ◽  
Case Based

Predictive Maintenance (PdM) at the PLN Power Plant is a periodic monitoring of equipment activities before the equipment is damaged in more severe conditions. According to an expert or PdM owner that maintenance analysis is not appropriate and efficiency has an impact on maintenance costs that are not small. In real conditions, the PdM owner analyzes equipment damage based on previous cases of damage equipment. Then we need a computer-based intelligent system that can help detect damage to equipment.Based on the Literature Review that has been done, Case-Based Reasoning can solve new problems using answers or experiences from old problems such as imitating human abilities. Case-Based Reasoning Process there is the most important step, which is to find the highest similarity value or the level of similarity between new cases and old cases by adapting solutions from old cases that have occurred (Sankar, 2004). In this study the process of similarity or approach using Nearest Neighbor.Testing on the system uses 20 test data and the measurement of system performance uses confusion matrix. Evaluation of testing using confusion matrix can be seen how accurately the system can classify data correctly that is equal to 97.98%. Then the precision value of 95% represents the number of positive categorized data that is correctly divided by the total data classified as positive. Furthermore, the test results of the equipment damage detection test data at the PLN plant with a threshold value of 0.75 using the nearest neighbor, the system has a performance with a 95% sensitivity level.

Intelligent Tool for the Design of Electrical Connectors

2013 ◽  
Vol 336-338 ◽  
pp. 1344-1348
Author(s):  
S.C. Fok ◽  
Fock Lai Tan
Keyword(s):  
Intelligent System ◽  
Automatic Generation ◽  
Case Based Reasoning ◽  
Electrical Connector ◽  
Conceptual Designs ◽  
Fixed Topology ◽  
Case Based ◽  
Electrical Connectors

The paper describes an intelligent system for the automatic generation of electrical connector designs. A framework for the system is proposed based on the case-based reasoning approach. The work aims to improve the productivity through automatic exploration of the electronic CAD drawings and reuse successful past solutions for the generation of new conceptual designs. Although this paper focuses on the connector designs, the fundamentals could be applicable to other products that contain distinct sub-components confined within a fixed topology.

scholarly journals Case based Reasoning Prediksi Waktu Studi Mahasiswa Menggunakan Metode Euclidean Distance dan Normalisasi Min-Max

2020 ◽  
Vol 7 (6) ◽  
pp. 1279
Author(s):  
Henni Endah Wahanani ◽  
Made Hanindia Prami Swari ◽  
Fawwaz Ali Akbar
Keyword(s):  
Euclidean Distance ◽  
Intelligent System ◽  
Accurate Method ◽  
Case Based Reasoning ◽  
Study Program ◽  
A Value ◽  
Student Graduation ◽  
Case Data ◽  
Precision Testing ◽  
Case Based

<p>Salah satu penyebab dari lamanya waktu tempuh mahsiswa di Jurusan Informatika UPN “Veteran” Jawa Timur adalah sullitnya memantau kemajuan studi mahasiswa secara seksama, mengingat jumlah mahasiswa yang cukup banyak serta pihak akademik belum memiliki metode yang akurat untuk memetakan mahasiswa yang diprediksi akan mengalami keterlambatan dalam penyelesaian studinya. Melalui perkembangan teknologi informasi yang berkembang pesat saat ini, maka sangat dimungkinkan untuk membuat sebuah sistem yang mampu memprediksi kemungkinan keterlambatan kelulusan mahasiswa melalui penggunaan berbagai metode komputasi yang ada. Salah satu pendekatan yang dapat digunakan untuk membuat sebuah sistem prediksi kelulusan adalah menggunakan pendekatan populer yang digunakan dalam pembuatan sistem cerdas <em>(intelligent system) </em>yaitu <em>case based reasoning </em>(CBR). Langkah-langkah yang dilakukan pada penelitian ini adalah melakukan pengumpulan dan memasukkan data kasus pada basis kasus, melakukan praprosesing yakni normalisasi atribut yang akan digunakan dalam perhitungan similartitas antar kasus menggunakan normalisasi min-max, implementasi CBR menggunakan metode Euclidean Distance, serta melakukan pengujian pada 141 data kasus. Dari sisi perhitungan akurasi, sistem mampu memberikan nilai akurasi paling tinggi sebesar 100% pada pada pengujian berdasarkan predikat kelulusan, sedangkan berdasarkan ketepatan waktu, sistem mampu memberikan akurasi tertinggi dengan nilai 85,71%, dan sistem mampu memberikan nilai akurasi tertinggi sebesar 71,43% pada pengujian berdasarkan massa studi. Untuk pengujian presisi, sistem mampu mengasilkan nilai terbesar berturut-turut sebesar 90,90%, 43,33%, dan 100%. Sedangkan pada pengujian sensitivitas, sistem berturut-turut mampu menghasilan nilai sebesar 90,90%, 40,48%, dan 100%. Hasil pengujian ini tentunya sangat bergantung dari basis kasus yang dimiliki, oleh sebab itu perbaikan dan peningkatan jumlah kasus yang dimiliki diharapkan mampu meningkatkan performa sistem rekomendasi.</p><p> </p><p><strong><em>Abstract</em></strong></p><p class="Judul2"><em>One of the reasons for the length of study time for students of the Informatics study program of UPN "Veteran" </em><em>Jawa Timur</em><em> is the difficulty of monitoring the progressy, given the large number of students and academics do not have an accurate method to map students who are predicted to experience delays. </em><em>I</em><em>t is possible to create a system that is able to predict the possibility of student graduation delay through the use of various existing computational methods. One approach that can be used to create a graduation prediction system is to use the popular approach namely case based reasoning (CB).</em><em> </em><em>The steps taken in this study are collecting and entering case data, normalizing the attributes using min-max normalization, implementing CBR using the Euclidean Distance, and system testing</em><em> in 141 data case</em><em>.</em><em> </em><em>Sy</em><em>stem is able to provide the highest accuracy value of 100% in testing based on the predicate of graduation, while based on timeliness, the system is able to provide the highest accuracy value with a value of 85.71%, and the system is able to provide the highest accuracy value of 71.43%. on testing based on the study period. For precision testing, the system was able to produce the largest values of 90.90%, 43.33% and 100%, respectively. Whereas in the sensitivity test, the system was able to produce values of 90.90%, 40.48%, and 100% respectively. The results of this test are of course very dependent on the basis of cases that are owned, therefore improvements and an increase in the number of cases owned are expected to be able to improve the performance.</em></p><p><strong><em><br /></em></strong></p>

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