scholarly journals A Mixed Rough Sets/Fuzzy Logic Approach for Modelling Systemic Performance Variability with FRAM

2020 ◽  
Vol 12 (5) ◽  
pp. 1918
Author(s):  
Hussein Slim ◽  
Sylvie Nadeau
Keyword(s):  
Fuzzy Logic ◽  
Rough Sets ◽  
Assessment Model ◽  
Rule Base ◽  
Data Sets ◽  
Mathematical Framework ◽  
Real World Data ◽  
Second Stage ◽  
Fuzzy Logic Approach ◽  
Input Variables

The task to understand systemic functioning and predict the behavior of today’s sociotechnical systems is a major challenge facing researchers due to the nonlinearity, dynamicity, and uncertainty of such systems. Many variables can only be evaluated in terms of qualitative terms due to their vague nature and uncertainty. In the first stage of our project, we proposed the application of the Functional Resonance Analysis Method (FRAM), a recently emerging technique, to evaluate aircraft deicing operations from a systemic perspective. In the second stage, we proposed the integration of fuzzy logic into FRAM to construct a predictive assessment model capable of providing quantified outcomes to present more intersubjective and comprehensible results. The integration process of fuzzy logic was thorough and required significant effort due to the high number of input variables and the consequent large number of rules. In this paper, we aim to further improve the proposed prototype in the second stage by integrating rough sets as a data-mining tool to generate and reduce the size of the rule base and classify outcomes. Rough sets provide a mathematical framework suitable for deriving rules and decisions from uncertain and incomplete data. The mixed rough sets/fuzzy logic model was applied again here to the context of aircraft deicing operations, keeping the same settings as in the second stage to better compare both results. The obtained results were identical to the results of the second stage despite the significant reduction in size of the rule base. However, the presented model here is a simulated one constructed with ideal data sets accounting for all possible combinations of input variables, which resulted in maximum accuracy. The same should be further optimized and examined using real-world data to validate the results.

Fuzzy logic approach for investigation of microstructure and mechanical properties of Sn96.5-Ag3.0-Cu0.5 lead free solder alloy

2017 ◽  
Vol 29 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Muhammad Aamir ◽  
Izhar Izhar ◽  
Muhammad Waqas ◽  
Muhammad Iqbal ◽  
Muhammad Imran Hanif ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Fuzzy Logic ◽  
Solder Alloy ◽  
Thermal Aging ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Content Type ◽  
Wide Range ◽  
Fuzzy Logic Approach ◽  
Free Solder

Purpose This paper aims to develop a fuzzy logic-based algorithm to predict the intermetallic compound (IMC) size and mechanical properties of soldering material, Sn96.5-Ag3.0-Cu0.5 (SAC305) alloy, at different levels of temperature. The reliability of solder joint in materials selection is critical in terms of temperature, mechanical properties and environmental aspects. Owing to a wide range of soldering materials available, the selection space finds a fuzzy characteristic. Design/methodology/approach The developed algorithm takes thermal aging temperature for SAC305 alloy as input and converts it into fuzzy domain. These fuzzified values are then subjected to a fuzzy rule base, where a set of rules determines the IMC size and mechanical properties, such as yield strength (YS) and ultimate tensile strength (UTS) of SAC305 alloy. The algorithm is successfully simulated for various input thermal aging temperatures. To analyze and validate the developed algorithm, an SAC305 lead (Pb)-free solder alloy is developed and thermally aged at 40, 60 and 100°C temperature. Findings The experimental results indicate an average IMCs size of 5.967 (in Pixels), 19.850 N/mm2 YS and 22.740 N/mm2 UTS for SAC305 alloy when thermally aged at an elevated temperature of 140°C. In comparison, the simulation results predicted 5.895 (in Pixels) average IMCs size, 19.875 N/mm2 YS and 22.480 N/mm2 UTS for SAC305 alloy at 140°C thermally aged temperature. Originality/value From the experimental and simulated results, it is evident that the fuzzy-based developed algorithm can be used effectively to predict the IMCs size and mechanical properties of SAC305 at various aging temperatures, for the first time.

A Fuzzy Logic Based Rocket Launch Tube’s DFMEA

2011 ◽  
Vol 87 ◽  
pp. 119-122
Author(s):  
Tosapolporn Pornpibunsompop ◽  
Attapon Charoenpon ◽  
Ekaratch Pankaew
Keyword(s):  
Fuzzy Logic ◽  
Failure Modes ◽  
Mechanical Load ◽  
Material Selection ◽  
Early Stage ◽  
Rule Base ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Potential Failure ◽  
Launch Tube

DFMEA is a significantly efficient tool to systematically evaluate risk in early stage of product design and development but some of knowledge and information are uncertain and imprecise. This research focuses on fuzzy logic approach to diminish weaknesses and applies to launch tube’s DFMEA. The methodology started from determine membership function of severity, occurrence, and detection and provide fuzzy rule base to arranged category of risk. Afterwards, center average index was selected as defuzzifier for risk value representation. Consequently, the prioritization based on risk value was done and chosen the first five risk value of potential failure modes to analyze causes then recommended appropriate actions. After application of fuzzy logic approach, the most vital potential failure mode is damaged launch tube due to detention force which is rated as first and second priority depending on potential cause or mechanism. The third priority is launch tube distortion. The mechanical load calculation and proper material selection are the recommended actions for overcoming those potential failure modes.

scholarly journals Parametric Rough Sets with Application to Granular Association Rule Mining

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Xu He ◽  
Fan Min ◽  
William Zhu
Keyword(s):  
Recommender Systems ◽  
Association Rule ◽  
Rough Sets ◽  
Relational Databases ◽  
Data Sets ◽  
Rule Mining ◽  
Real World Data ◽  
New Model ◽  
New Type ◽  
Two Universes

Granular association rules reveal patterns hidden in many-to-many relationships which are common in relational databases. In recommender systems, these rules are appropriate for cold-start recommendation, where a customer or a product has just entered the system. An example of such rules might be “40% men like at least 30% kinds of alcohol; 45% customers are men and 6% products are alcohol.” Mining such rules is a challenging problem due to pattern explosion. In this paper, we build a new type of parametric rough sets on two universes and propose an efficient rule mining algorithm based on the new model. Specifically, the model is deliberately defined such that the parameter corresponds to one threshold of rules. The algorithm benefits from the lower approximation operator in the new model. Experiments on two real-world data sets show that the new algorithm is significantly faster than an existing algorithm, and the performance of recommender systems is stable.

scholarly journals Penempatan Posisi Multi Kamera Berdasarkan Gaya Sutradara Berbasis Logika Fuzzy

2018 ◽  
Vol 5 (6) ◽  
pp. 687
Author(s):  
Hartarto Junaedi ◽  
Jaya Pranata ◽  
Mochamad Hariadi ◽  
I Ketut Eddy Purnama
Keyword(s):  
Fuzzy Logic ◽  
Computer Games ◽  
Computer Game ◽  
Point Of View ◽  
Virtual Camera ◽  
Fuzzy Logic Approach ◽  
Multi Agent ◽  
Logic Approach ◽  
Input Variables ◽  
Game Simulation

<p class="Abstrak">Teknologi komputer saat ini telah banyak digunakan dalam pengembangan animasi atau permainan komputer. Salah satu teknologi itu adalah <em>machinima </em>yaitu suatu sistem yang menggunakan teknologi mesin grafik 3D untuk menghasilkan produk sinematik secara <em>real time</em>. Dalam proses pembuatan produk sinematik itu penempatan posisi kamera sangat memegang peranan penting. Penempatan posisi kamera ini tentu harus sesuai dengan kaidah-kaidah sinematografi. Penelitian ini akan mengusulkan sebuah pendekatan agen cerdas dengan multi perilaku untuk menempatkan kamera <em>virtual</em> dalam lingkungan <em>virtual </em>secara otomatis sesuai dengan gaya seorang sutradara. Setiap kamera <em>virtual </em>itu akan memiliki perilaku yang berbeda berdasarkan kaidah sinematografi sehingga memiliki <em>Point of View</em> (POV) yang berbeda. Untuk memberikan perilaku pada kamera <em>virtual</em> akan digunakan pendekatan berbasis logika fuzzy dengan menggunakan metode <em>mamdani</em>. Jumlah variabel masukan yang digunakan sejumlah tiga dan variabel keluaran sejumlah tiga dengan <em>membership function </em>antara tiga sampai lima. Penelitian ini akan menggunakan simulasi permainan komputer dengan tiga kamera <em>virtual</em> dengan perilaku yang berbeda untuk merekam adegan yang sama dan hasilnya akan divalidasi berdasarkan hasil pengamatan dengan komunitas juru foto.  Pada akhirnya dapat diambil kesimpulan bahwa pendekatan logika fuzzy dapat digunakan untuk memberikan sebuah perilaku atau gaya sutradara pada kamera <em>virtual</em>.</p><p class="Abstrak"><strong>Abstract</strong></p><p class="Abstract">Computer technology is has been used widely in the development of animation or computer games. One of the technologies is machinima, a system that uses reak time 3D graphics engine technology to produce cinematic products. In the process of develop a cinematic product, camera positioning is a very important component. The camera positioning must be comply with cinematography’s rule. This research will propose an intelligent multi agent behavior to positining a virtual camera in a virtual environment automatically according to the director’s style. Each virtual camera will have a different behavior based on cinematographic rules so that it has a different Point of View (POV). To assign a behavior on the virtual camera will be based on  fuzzy logic using the mamdani method. The number of input variables are three and the output variables are three with the number membership functions between three to five. This research will program  a computer game simulation with three multi behavior virtual cameras to capture some scene and the results will be validated based on observations with the photographer community. Finally it can be concluded that the fuzzy logic approach can be used to assign some behavior to a virtual camera.</p>

Fuzzy Analysis of Speech Metrics to Estimate Conductor Alertness

2009 ◽  
Author(s):  
Parham Shahidi ◽  
Steve C. Southward ◽  
Mehdi Ahmadian
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Rule Base ◽  
Mathematical Framework ◽  
Human Knowledge ◽  
Knowledge Based ◽  
Single Output ◽  
Output System ◽  
Alertness Level ◽  
Different Levels

A Fuzzy Logic-based algorithm has been developed for processing a series of speech metrics with the ultimate goal of estimating train conductor alertness. The output is a single metric, which directly quantifies the alertness level of the conductor. The metrics were selected based on their correlation to alertness through processed speech, but without any interpretation of the spoken words or phrases. Metrics that are used include: speech duration, silence duration, word production rate and word intensity. The assessment of these metrics is an experience and human knowledge based task, which generates the need for a mathematical model to accommodate this special circumstance. The algorithm developed here uses Fuzzy Logic to cast the human knowledge base into a mathematical framework for the alertness estimation analysis. The core of this fuzzy system is a rule base consisting of fuzzy IF-THEN rules, which are derived from the existing knowledge about the effects of sleep deprivation on alertness such as Furthermore, the rules were inferred from actual voice recordings that were taken on board a train. This data was then used to create a classification scheme to determine which pattern in the speech indicates different levels of alertness from anxiety to fatigue. The simplicity of the underlying mathematical model in this approach enables this system to compute and output an alertness metric in real-time. The nature of this algorithm allows for the use of an arbitrary number of rules to classify the alertness level and therefore provides the ability to continuously develop and extend the rule base as new knowledge emerges. The resulting algorithm is a fast, multi-input, single-output system that is able to quantify the train conductor’s alertness level anytime speech is produced.

scholarly journals A Proposition for Combining Rough Sets, Fuzzy Logic and FRAM to Address Methodological Challenges in Safety Management: A Discussion Paper

Safety ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. 50
Author(s):  
Hussein Slim ◽  
Sylvie Nadeau
Keyword(s):  
Fuzzy Logic ◽  
Rough Sets ◽  
Safety Management ◽  
Sociotechnical Systems ◽  
Rule Base ◽  
Generation Process ◽  
Discussion Paper ◽  
Advantages And Disadvantages ◽  
Resonance Analysis ◽  
Third Phase

In recent years, the focus in safety management has shifted from failure-based analysis towards a more systemic perspective, redefining a successful or failed performance as a complex and emergent event rather than as a conclusion of singular errors or root causes. This paradigm shift has also necessitated the introduction of innovative tools capable of capturing the complex and dynamic nature of modern sociotechnical systems. In our research, we argued at previous stages for adopting a more systemic and human-centric perspective to evaluate the context of aircraft de-icing operations. The Functional Resonance Analysis Method (FRAM) was applied in the first stage for this purpose. Consequently, fuzzy logic was combined with FRAM in the second stage to provide a quantified representation of performance variability. Fuzzy logic was used as a quantification tool suitable for computing with natural language. Several limitations were found in the data collection and rule generation process for the first prototype. In the third phase, the model was further improved by integrating rough sets as a data-mining tool to generate and reduce the size of the rule base and classify outcomes. In this paper, we reflect on the three stages of the project and discuss in a qualitative manner the challenges and limitations faced in the development and application of the models. A summary of the advantages and disadvantages of the three models as experienced in our case are presented at the end. The objective is to present an outlook for future studies to address methodological limitations in the study of complex sociotechnical systems.

scholarly journals Using Fuzzy Logic to Adjust Plasma Concentration Based on a Two-Compartment Pharmacokinetic Model

2013 ◽  
Vol 341-342 ◽  
pp. 1171-1174
Author(s):  
Lei Zhao ◽  
Xin Ling Shi ◽  
Yu Feng Zhang ◽  
Ya Jie Liu
Keyword(s):  
Fuzzy Logic ◽  
Pharmacokinetic Model ◽  
Fuzzy Controller ◽  
Reference Value ◽  
Rule Base ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Input Variables ◽  
Adaptation Scheme

In this paper, a closed-loop control system was developed using fuzzy logic to adapt the parameters of a pharmacokinetic (PK) model. The system is based on a two-compartment PK model with first-order rate process of oral administration. The fuzzy logic adaptation scheme uses the error and the change in error as the input variables. The output variable of the fuzzy controller is the scaling factor to adjust the PK parameter. The fuzzy controller adjusted the real situation concentration to the reference value derived from the parameters of population mean data according to the established rule-base. The simulation results show that the controller provides good performance to adjust the concentration with the reference values.

scholarly journals RANCANGAN MODEL PERFORMANSI RISIKO RANTAI PASOK AGROINDUSTRI SUSU DENGAN MENGGUNAKAN PENDEKATAN LOGIKA FUZZY (A Supply Chain Risk Performance Model for Local Raw Milk Agro-Industry Based on Fuzzy Logic Approach)

2015 ◽  
Vol 35 (01) ◽  
pp. 88 ◽  
Author(s):  
Winnie Septiani ◽  
Taufik Djatna
Keyword(s):  
Fuzzy Logic ◽  
Supply Chain ◽  
Dairy Product ◽  
Inference Engine ◽  
Risk Exposure ◽  
Rule Base ◽  
Time Cost ◽  
Exposure Risk ◽  
Second Stage ◽  
The Impact

The critical point of performance and risk supply chain in a dairy product agro-industries was found in the product’s perishable characteristics. Bacterial and antibiotic contaminations have been identified as the major risks. This risks arise from a series of activities strarting from farms, cooperatives and Milk Processing Industry that will affect the entire supply chain performance. This paper aimed to design performance and risk supply chain model for agroindustrial dairy product supply chain risks by using Fuzzy Associative Memories (FAMS) approach. The approach isused to translate a quantity that is expressed using the language (linguistic). The fuzzy logic system provides fourbasic elements, namely :  (i) rule base; (ii) inference engine; (iii) fuzzification; (iv) defuzzification. There are three proposed components in the model, namely : (i) performance profile; (ii) risk profile and (iii) risk exposure, which were expressed in time, cost and quality. Theinitial stage began with the analysis of invetible exposure risk exposure,including analysis of environmental and configuration characteristics, as well as dairy agro-industries supply chain. The second stage wasanalysis of evitable exposure risk, while the third stage was to change, risk exposure into time, cost and quality performance units. The second stage generateds risk magnitude of risk as a function of probability andseverity, the two value that were measured with Fuzzy AssociativeMemories (FAMS). The Model, therefore  showed the  impact of emerging risks damage to the agro-industry supply chain, which could be measured and be minimized in order to improve the robustnesss of the supply chain.Keywords: Performance, risk, fuzzy, supply chain, dairy agroindustry ABSTRAKTitik kritis dari performansi dan risiko rantai pasok agroindustri susu terletak pada karakteristik produknya yang mudah rusak. Risiko tertinggi yang teridentifikasi pada rantai ini adalah risiko susu terkontaminasi bakteri dan antibiotik. Risiko ini muncul dari rangkaian aktivitas yang terjadi mulai dari peternakan, koperasi dan Industri Pengolahan Susu (IPS) yang akan mempengaruhi performasi rantai pasok keseluruhan. Paper ini bertujuan untuk merancang model performansi dan risiko rantai pasok agroindustri susu dengan menggunakan pendekatan Fuzzy Assosiated Memories (FAMs). Logika fuzzy digunakan untuk menerjemahkan suatu besaran yang diekspresikan menggunakan bahasa (linguistic). Secara umum dalam sistem logika fuzzy terdapat empat buah elemen dasar, yaitu: basis kaidah (rule base), mekanisme pengambilan keputusan (inference engine), proses fuzzifikasi (fuzzification) dan proses defuzzifikasi (defuzzification). Ada tiga komponen yang dipertimbangkan dalam rancangan model yaitu profil performansi, profil risiko dan eksposurrisiko dalam ukuran waktu, biaya dan kualitas. Tahap pertama dimulai dengan menganalisis eksposur risiko yang tidak terhindarkan yang meliputi analisis karakteristik lingkungan dan konfigurasi serta karakteristik rantai pasok agroindustri susu. Tahap kedua adalah menganalisis eksposure risiko yang dapat dihindari. Tahap ketiga adalah mengubah eksposur risiko ke dalam ukuran performansi waktu, biaya dan kualitas. Pada tahap kedua dihasilkan magnitude risiko, yang merupakan fungsi dari nilai probabilitas dan severity yang dilakukan dengan menggunakan Fuzzy Assosiated Memories (FAMs).Dengan model ini diharapkan dampak kerusakan dari risiko yang muncul pada rantai pasok agroindustri susu dapat terukur dan dapat diminimasi sehingga dapat meningkatkan ketangguhan (robustnes) dari rantai pasok.Kata kunci: Performansi, risiko, fuzzy, rantai pasok, agroindustri susu

Pattern classification using grey tolerance rough sets

Kybernetes ◽  
2016 ◽  
Vol 45 (2) ◽  
pp. 266-281 ◽  
Author(s):  
Yi-Chung Hu
Keyword(s):  
Similarity Measure ◽  
Rough Set ◽  
Rough Sets ◽  
Classification Performance ◽  
Data Sets ◽  
Real World Data ◽  
Content Type ◽  
Tolerance Rough Set ◽  
Grey Relational ◽  
The Relationship

Purpose – The purpose of this paper is to propose that the grey tolerance rough set (GTRS) and construct the GTRS-based classifiers. Design/methodology/approach – The authors use grey relational analysis to implement a relationship-based similarity measure for tolerance rough sets. Findings – The proposed classification method has been tested on several real-world data sets. Its classification performance is comparable to that of other rough-set-based methods. Originality/value – The authors design a variant of a similarity measure which can be used to estimate the relationship between any two patterns, such that the closer the relationship, the greater the similarity will be.

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