Fuzzy Expert System

Fault diagnosis of industrial machineries become very much important for improving the quality of the manufacturing as well as for reducing the cost for product testing. In modern manufacturing scenario, a fast and reliable diagnosis system has turned into a challenging issue in the complex industrial environment. In this work, the diagnosis of gearbox is considered as a mean of health monitoring system by used lubricant. The proposed methodology has been performed on the basis of wear particle analysis in gearbox at offline stage. Possible wear characterization has been done by image vision system to interpret into soft computing techniques like fuzzy inference and neural network mechanisms. Basically, the maintenance policy has been taken with the help of fuzzy expert system, which has been described in the present work.

Social media is said to have an impact on the public discourse and communication in the society. It is increasingly being used in the political context. Social networks sites such as Facebook, Twitter and other microblogging services provide an opportunity for public to give opinions about some issues of interest. Twitter is an ideal platform for users to spread not only information in general but also political opinions, whereas Facebook provides the capability for direct dialogs. A lot of studies have shown that a need exists for stakeholders to collect, monitor, analyze, summarize and visualize these social media views. Some authors have tended to categorize these comments as either positive or negative ignoring the neutral category. In this paper, we demonstrate the importance of the neutral category in the clustering of sentiments from the social media. We then demonstrate the use of fuzzy clustering for this kind of task.

Following type-1 fractional fuzzy inference systems presented recently as the new generation of fuzzy inference systems, interval type-2 fractional fuzzy inference systems (IT2FFISs) as a leap further ahead in the evolution of fuzzy inference systems (FISs) are introduced in this article. The IT2FFISs, which are outlined in this article, add to the armamentarium of FISs some particular concepts such as interval type-2 fractional membership functions, type-2 fractional translation rule, type-2 fracture index, the concept of switching, the entanglement, the degeneracy concept, and so forth. An IT2FFIS exploits not only the tolerance for the uncertainty in the interpretation of the meaning of a word, but also the relevance between the quality and quantity levels of the given information to infer an answer to an inference query. The IT2FFISs make an increase in machine intelligence quotient possible by an increase in the range of FISs order rather than their type. Moreover, the synergy of the concepts coming with various modes of IT2FFISs such as the aggressive mode opens a gate to a space of fuzzy systems outputs which used to be indiscoverable. Furthermore, it is demonstrated that as the type-2 fracture index approaches zero, the space of IT2FFISs outputs contracts and eventually it coincides the space of IT2FISs output when the fracture index is equal to zero. It is also proved that, provided a particular order of the IT2FFIS is taken into account, independent of the problem in question, a typical IT2FIS never leads to results which are more satisfactory than those obtained by the IT2FFIS corresponding to the typical IT2FIS.

Abstract—Human disease diagnosis is a complicated process and requires high level of expertise. Any attempt of developing a web-based expert system dealing with human disease diagnosis has to overcome various difficulties. This paper describes a project work aiming ...

The theory of dual numerical means of random and experienced variables is briefly described in the framework of the new theory of experience and the chance that arises as an axiomatic synthesis of two dual theories — the Kolmogorov theory of probability and the theory of believability. A new term is introduced for the numerical mean of the experienced variable — mathematical reflection, which is dual to the mathematical expectation of a random variable within the framework of the new theory. The basic properties and examples of dual numerical means are considered.

The warm and humid condition is the characteristic of Malaysia tropical climate. Prediction of rain occurrences is important for the daily operations and decisions for the country that rely on agriculture needs. However predicting rainfall is a complex problem because it is effected by the dynamic nature of the tropical weather parameters of atmospheric pressure, temperature, humidity, dew point and wind speed. Those parameters have been used in this study. The rainfall prediction are compared and analyzed. Fuzzy Logic and Fuzzy Inference System can deal with ambiguity that often occurred in meteorological prediction; it can easily incorporate with expert knowledge and empirical study into standard mathematical. This paper will determine the dependability of Fuzzy Logic approach in rainfall prediction within the given approximation of rainfall rate, exploring the use of Fuzzy Logic and to develop the fuzzified model for rainfall prediction. The accuracy of the proposed Fuzzy Inference System model yields 72%

Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are categorized into three techniques of recommender system, i.e.; collaborative filtering (CF), content based and context based. We have tried to find out the research papers related to sentimental analysis based recommender system. To classify research done by authors in this field, we have shown different approaches of recommender system based on sentimental analysis with the help of tables. Our studies give statistics, approximately trends in recommender structures research, and gives practitioners and researchers with perception and destiny route on the recommender system using sentimental analysis. We hope that this paper enables all and sundry who is interested in recommender systems research with insight for destiny.

For a long time, one of my dreams was to describe the nature of uncertainty axiomatically, and it looks like I've finally done it in my co∼eventum mechanics! Now it remains for me to explain to everyone the co∼eventum mechanics in the most approachable way. This is what I'm trying to do in this work. The co∼eventum mechanics is another name for the co∼event theory, i.e., for the theory of experience and chance which I axiomatized in 2016 [1, 2]. In my opinion, this name best reflects the co∼event-based idea of the new dual theory of uncertainty, which combines the probability theory as a theory of chance, with its dual half, the believability theory as a theory of experience. In addition, I like this new name indicates a direct connection between the co∼event theory and quantum mechanics, which is intended for the physical explanation and description of the conict between quantum observers and quantum observations [4]. Since my theory of uncertainty satises the Kolmogorov axioms of probability theory, to explain this co∼eventum mechanics I will use a way analogous to the already tested one, which explains the theory of probability as a theory of chance describing the results of a random experiment. The simplest example of a random experiment in probability theory is the " tossing a coin ". Therefore, I decided to use this the simplest random experiment itself, as well as the two its analogies: the " "flipping a coin " and the " spinning a coin " to explain the co∼eventum mechanics, which describes the results of a combined experienced random experiment. I would like to resort to the usual for the probability theory " coin-based " analogy to explain (and first of all for myself) the logic of the co∼eventum mechanics as a logic of experience and chance. Of course, this analogy one may seem strange if not crazy. But I did not come up with a better way of tying the explanations of the logic of the co∼eventum mechanics to the coin-based explanations that are commonly used in probability theory to explain at least for myself the logic of the chance through a simple visual " coin-based " model that clarifies what occurs as a result of a combined experienced random experiment in which the experience of observer faces the chance of observation. I hope this analogy can be useful not only for me in understanding the co∼eventum mechanics.

Prediction of signal strength received in certain locations in wetland and dryland areas is of paramount importance in the determination of the performance of any wireless design. In this paper, the significance of the Okumura-Hata model is investigated for the 4G signal. The received signal strengths at different locations for three (3) 4G base stations in Lagos are measured through the drive test. Some of the existing propagation path loss models such as Free Space, Okumura, Okumura-Hata, COST 231 Hata, Davidson-Hata are not suitable for prediction of 4G signal in Lagos, Nigeria due to a high error caused by higher carrier frequency and distance. The analysis of the Okumura-Hata model is carried out and compared with the measured values. Path loss obtained for Isolo (urban dryland), Itoikin (Suburban wetland) and Ijede (Rural dryland) respectively. The dry land areas of Isolo and Ijede revealed a very close mean square error relationship of 20.56dB and 22.22dB. The wetland protected area of Itoikin has a low mean square error of 12.51dB. The ECC-33 model has a very high mean square error making it not a suitable model for both wetland and dryland areas. For April, the path loss for Isolo was slightly above 200dB while that of Itoikin which happen to be a wetland terrain is above 250dB. The path loss of Ijede was also about 250dB and the reason is that Ijede is near to water environment.

The absence of prediction system that can provide prediction analysis on the graduation rate of students becomes the reason for the research on the prediction of the level of graduation rate of students. The number of students who graduate on time becomes indicator of success of universities. Many studies on predicting students on time graduation have been conducted. The Fuzzy K-Nearest Neighbor, a method to classify objects based on training data located closest to the object, and using data from teknokrat universities student graduates in 2009 until 2013 faculties of engineering and computer science was used in this study. Selection of the value of k in KNN algorithm became important because it would affect the performance of the algorithm KNN. Based on the results of measuring the performance of the algorithm by using cross validation, confusion matrix, it was found the value of k = 10 and the fuzzy K-Nearest Neighbor had an accuracy value of 77,35%. 1. PENDAHULUAN Data Mining didefinisikan sebagai proses penemuan pola dalam data. Berdasarkan tugasnya, data mining dikelompokkan menjadi deskripsi, estimasi, prediksi, klasifikasi, clustering dan asosiasi.[6] Selain itu data mining merupakan salah satu teknik yang dapat melakukan prediksi dengan teknik penggalian data. Penggalian data berdasarkan data pendidikan di universitas dapat meningkatkan kualitas pembelajaran Mahasiswa di universitas. Melakukan Prediksi Tentang prediksi tingkat kelulusan Mahasiswa sangatlah penting dimana informasi yang dihasilkan oleh hasil prediksi ini dapat dijadikan sebagai bahan pertimbangan bagi pihak manajemen program studi untuk melakukan langkah secara persuasif dalam rangka meningkatkan persentasi kelulusan Mahasiswa yang memenuhi standar mutu yang telah ditetapkan kampus. Prediksi dalam bentuk komputasi merupakan satu kegiatan matematis. Prediksi ini telah dilakukan bertahun-tahun sebelum penguasaan komputer, yaitu menggunakan kalkulator. Prediksi tingkat kelulusan Mahasiswa dapat membantu pihak manajemen dalam mengambil keputusan. Bagaimana menganalisa kelulusan Mahasiswa dan mendapatkan parameter terbaik dari metode yang digunakan untuk dapat memprediksi kelulusan Mahasiswa. Sebuah penelitian membahas tentang Analisis Prediksi Tingkat Pengunduran Diri Mahasiswa dengan Metode K-Nearest Neighbor. Dimana dalam penelitian yang dilakukan oleh penulis mengangkat masalah mengenai pentingnya analisis prediksi tentang pengunduran diri Mahasiswa di STIKOM UYELINDO Kupang karena menentukan prediksi tingkat pengunduran diri Mahasiswa dalam jumlah besar tidak mungkin dilakukan secara manual karena membutuhkan waktu yang cukup lama. Untuk itu dibutuhkan sebuah algoritma yang dapat mengkategorisasikan prediksi tingkat pengunduran diri Mahasiswa secara otomatis menggunakan komputer. Hasil yang didapat dari penelitian ini yaitu bertujuan untuk menghasilkan sebuah data yang dapat diuji untuk mendapat prediksi dan keakuratan klasifikasi [8].

Since the term ''Fuzzy differential equations'' (FDEs) emerged in the literature in 1978, prevailing research effort has been dedicated not only to the development of the concepts concerning the topic, but also to its potential applications. This paper presents a chronological survey on fuzzy differential equations of integer and fractional orders. Attention is concentrated on the FDEs in which a definition of fuzzy derivative of a fuzzy number-valued function has been taken into account. The chronological rationale behind considering FDEs under each concept of fuzzy derivative is highlighted. The pros and cons of each approach dealing with FDEs are also discussed. Moreover, some of the proposed FDEs applications and methods for solving them are investigated. Finally, some of the future perspectives and challenges of fuzzy differential equations are discussed based on our personal view point.

International Journal of Fuzzy Logic Systems (IJFLS) is an open access peer reviewed journal that covers all topics in theoretical, experimental and applied fuzzy techniques and systems. It is aimed to bring together researchers and developers from both academia and industry to discuss the latest scientific and theoretical advances in this field, and to demonstrate the state-of-the-art systems. The journal solicits original technical papers that were not previously published and are not currently under review for publication elsewhere.

8th International Conference on Artificial Intelligence and Fuzzy Logic Systems (AIFZ 2022) is a forum for presenting new advances and research results in the fields of Artificial Intelligence and Fuzzy
Logic Systems. The conference will bring together leading researchers, engineers, and scientists in the domain of interest from around the world. The scope of the conference covers all theoretical and practical aspects of the Artificial Intelligence and Fuzzy Logic Systems. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences.

All submissions must describe original research, not published or currently under review for another conference or journal.

This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy inference systems (FIS) using five well known computational frameworks: genetic-fuzzy systems (GFS), neuro-fuzzy systems (NFS), hierarchical fuzzy systems (HFS), evolving fuzzy systems (EFS), and multiobjective fuzzy systems (MFS), which is in view that some of them are linked to each other. The heuristic design of GFS uses evolutionary algorithms for optimizing both Mamdani-type and Takagi-Sugano-Kang-type fuzzy systems; whereas, the NFS combines the FIS with neural network learning method to improve the approximation ability. HFS combines two or more low-dimensional fuzzy logic units in a hierarchical design to overcome the curse of dimensionality. EFS solves the data streaming issues by refining (evolving) the system incrementally, and MFS solves the multi-objective trade-offs like the simultaneous maximization of both interpretability and accuracy. The overall synthesis of these dimensions explores the FIS's potential challenges and opportunities ; the complex relations among the dimension; and the FIS's potential to combining one or more computational frameworks adding another dimension: deep fuzzy systems.

org/fuzzy/index Scope & Topics 8 th International Conference on Fuzzy Logic Systems (Fuzzy 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology, and applications of Fuzzy Logic Systems. The Conference looks for significant contributions to all major fields of the Fuzzy Logic Systems in theoretical and practicalaspects.

Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers' preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information.

Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM) problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution) method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems.

International Journal of Fuzzy Logic Systems (IJFLS) is an open access peer-reviewed journal that covers all topics in theoretical, experimental and applied fuzzy techniques and systems. It is aimed to bring together researchers and developers from both academia and industry to discuss the latest scientific and theoretical advances in this field, and to demonstrate the state-of-the-art systems. The journal solicits original technical papers that were not previously published and are not currently under review for publication elsewhere. Topics of Interest  Fuzzy logic techniques & Algorithm  Fuzzy mathematics  Fuzzy measure and integral  Type 2 fuzzy Logic  Possibility theory and imprecise probability  Fuzzy database  Fuzzy Clustering  Fuzzy decision support system  Fuzzy expert system  Fuzzy mathematical programming  Fuzzy decision making and decision support systems  Fuzzy modeling and fuzzy control of biotechnological processes  Fuzzy neural systems, neuro-fuzzy systems  Fuzzy systems modeling and identification  Fuzzy pattern recognition  Fuzzy process control  Fuzzy reasoning system  Fuzzy-rule based system  Fuzzy System in Multimedia and web-based applications  Fuzzy system applications in computer vision  Hybrid fuzzy systems (fuzzy-neuro-evolutionary-rough)  Fuzzy system applications in e-commerce  Fuzzy sets in bioinformatics  Fuzzy system applications in human-machine interface  Fuzzy system applications in robotics  Fuzzy system applications in system and control engineering

Kecerdasan Buatan adalah salah satu cabang Ilmu pengetahuan berhubungan dengan pemanfaatan mesin untuk memecahkan persoalan yang rumit dengan cara yang lebih manusiawi. Hal Ini biasanya dilakukan dengan mengikuti/mencontoh karakteristik dan analogi berpikir dari kecerdasan/Inteligensia manusia, dan menerapkannya sebagai algoritma yang dikenal oleh komputer. Dengan suatu pendekatan yang kurang lebih fleksibel dan efisien dapat diambil tergantung dari keperluan, yang mempengaruhi bagaimana wujud dari perilaku kecerdasan buatan. AI biasanya dihubungkan dengan Ilmu Komputer, akan tetapi juga terkait erat dengan bidang lain seperti Matematika, Psikologi, Pengamatan, Biologi, Filosofi, dan yang lainnya. Kemampuan untuk mengkombinasikan pengetahuan dari semua  bidang ini pada akhirnya akan bermanfaat bagi kemajuan dalam upaya menciptakan suatu kecerdasan buatan.

Selection of an appropriate mining method is a complex task that requires consideration of many technical, economical, political, social, and historical factors. The aim of this paper is developing a hierarchical model to selection the optimum mining method with the use of effective and major criteria and simultaneously, taking subjective judgments of decision makers into consideration. Proposed approach is based on the combination of Fuzzy Analytic Hierarchy Process (FAHP)method with TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. FAHP is used in determining of the weights of the criteria by decision makers and then rankings of the methods are determined by TOPSIS. The proposed method is applied for Jajarm Bauxite Mine in Iran and finally the most appropriate mining methods for this mine are ranked.

The study of this paper suggests on dependency problem in fuzzy computational method by using the numerical solution of Fuzzy differential equations(FDEs) in Milne's predictor-corrector method. This method is adopted to solve the dependency problem in fuzzy computation. We solve some fuzzy initial value problems to illustrate the theory. KEYWORDS Fuzzy initial value problem, Dependency problem in fuzzy computation, Milnes predictor-corrector method.

Prediction about the result of cricket matches astonishing as a research problem, especially due to its complexity, unpredictable assumption (weather and pitch conditions). Because the ultimate outcome of a cricket match is based on many aspect and unaccepted bearings therefore it is difficult responsibility to predict the exact and partial truth-based outcomes of cricket matches such a research expects a multi criteria decision making approach. TOPSIS to predict true ranking and principally applied to fallouts of CRICKET WORLD CUP 2019. So, by proposed technique, India has the most chances of winning the CWC2019, and the rank of team Pakistan is 7. The team Afghanistan has the lowest chances of winning. .

Metode Mamdani sering juga dikenal dengan nama metode Max-Min. metode ini diperkenalkan oleh Ebrahim Mamdani pada tahun 1975 (Kusuma Dewi, 2003). Untuk medapatkan output diperlukan beberapa tahapan, antara lain:
• Pembentukan himpunan fuzzy
• Aplikasi fungsi implikasi
• Komposisi aturan

International Journal of Fuzzy Logic Systems (IJFLS) is an open access peer-reviewed journal that covers all topics in theoretical, experimental and applied fuzzy techniques and systems. It is aimed to bring together researchers and developers from both academia and industry to discuss the latest scientific and theoretical advances in this field, and to demonstrate the state-of-the-art systems. The journal solicits original technical papers that were not previously published and are not currently under review for publication elsewhere.

According to the huge criticality of using advanced software systems and the great demands of providing updated and qualified programs, this paper reflects some future perspectives towards the importance of software in managing everything in the world life over the next thirty years. Moreover, the paper presents the challenges which face the recent and the future generations as a result of this huge revolution of technology and automations. In addition to that, the writer would provide some solutions for those obstacles in order to enhance the role of software engineers in 2050. Also the paper reviews the related literature and surveys the point of view of software engineering experts by assigning an online interview with six open ended questions to examine their perspectives towards the future of Internet of things, Artificial intelligence, ubiquitous computing, and system of systems. The majority of ideas reflected the humanity fears of technology and replacing people with robots in the job fields. Furthermore, some experts encouraged the idea of having smart homes, and wearable devices Keywords: advanced Software; system of systems; 3D building printer, internet of things, artificial intelligence, ubiquitous computing, and system of systems.

This study considers the robust identification of the parameters describing a Sugeno type fuzzy inference system with uncertain data. The objective is to minimize the worst-case residual error using a numerically efficient algorithm. The Sugeno type fuzzy systems are linear in consequent parameters but nonlinear in antecedent parameters. The robust consequent parameters identification problem can be formulated as second-order cone programming problem. The optimal solution of this second-order cone problem can be interpreted as solution of a Tikhonov regularization problem with a special choice of regularization parameter which is optimal for robustness (Ghaoui and Lebret (1997). SAIM Journal of Matrix Analysis and Applications 18, 1035–1064). The final regularized nonlinear optimization problem allowing simultaneous identification of antecedent and consequent parameters is solved iteratively using a generalized Gauss–Newton like method. To illustrate the approach, several simulation studies on numerical examples including the modelling of a spectral data function (one-dimensional benchmark example) is provided. The proposed robust fuzzy identification scheme has been applied to approximate the physical fitness of patients with a fuzzy expert system. The identified fuzzy expert system is shown to be capable of capturing the decisions (experiences) of a medical expert.

The objectives of this study are the determination of forest fire risks with the fuzzy analytic hierarchy process (FAHP) and the mapping of risk levels with the use of geographic information systems (GIS). Socioeconomic, topographic, climatic, and stand structures have been taken into consideration as instrumental criteria in terms of fire risk. Each risk criteria and their sub-criteria membership grades have been
determined with the fuzzy set theory. Five-scale fuzzy linguistic importance has been used for pairwise comparison matrices. Criterion weights have been mapped with the use of GIS, and afinal risk map was established with weighted overlay analysis. Socioeconomic properties had the highest impact onfire risk with 35%. The high risk
degree of this criterion manifests in shrublands with substantial fuel loads and young Calabrian pine forests in low elevation areas at the edge of roads, urban and urban periphery areas, south sloping, and steep sloped areas. The lowest risk degree was manifest in stands of cedar, black pine, and juniper forests, qualifying as old growth
spreading in sub-mountain areas where land usage is rather low. Experiences regarding high accuracy fire risk determination and decision support approaches forfire risk management have been discussed and concluded in terms of applied FAHP and GIS procedures.