Search results for: fuzzy entropy

Authors: P. W. Tsai, J. W. Chen, C. W. Chen, C. Y. Chen

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In recent years, many researchers are involved in the field of fuzzy theory. However, there are still a lot of issues to be resolved. Especially on topics related to controller design such as the field of robot, artificial intelligence, and nonlinear systems etc. Besides fuzzy theory, algorithms in swarm intelligence are also a popular field for the researchers. In this paper, a concept of utilizing one of the swarm intelligence method, which is called Bacterial-GA Foraging, to find the stabilized common P matrix for the fuzzy controller system is proposed. An example is given in in the paper, as well.

Keywords: half-circle fuzzy numbers, predictions, swarm intelligence, Lyapunov method

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Authors: Mandar Ghodekar, Sharad Jadhav, Sangram Jadhav

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Speed control of rotor during startup and under varying load conditions is one of the most difficult tasks of gas turbine operation. In this paper, power plant gas turbine (GE9001E) is considered for this purpose and fuzzy and fuzzy-PI rotor speed controllers are designed. The goal of the presented controllers is to keep the turbine rotor speed within predefined limits during startup condition as well as during operating condition. The fuzzy controller and fuzzy-PI controller are designed using Takagi-Sugeno method and Mamdani method, respectively. In applying the fuzzy-PI control to a gas-turbine plant, the tuning parameters (Kp and Ki) are modified online by fuzzy logic approach. Error and rate of change of error are inputs and change in fuel flow is output for both the controllers. Hence, rotor speed of gas turbine is controlled by modifying the fuel ƒflow. The identified linear ARX model of gas turbine is considered while designing the controllers. For simulations, demand power is taken as disturbance input. It is assumed that inlet guide vane (IGV) position is fixed. In addition, the constraint on the fuel flow is taken into account. The performance of the presented controllers is compared with each other as well as with H∞ robust and MPC controllers for the same operating conditions in simulations.

Keywords: gas turbine, fuzzy controller, fuzzy PI controller, power plant

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work.

Keywords: Shannon entropy, multifractional Brownian motion, Hurst–Holder exponent, stock indexes

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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In this paper, a set of Filipino Phonetically Balanced Word list consisting of 250 words (PBW250) were constructed for a phoneme-level ASR system for the Filipino language. The Entropy Maximization is used to obtain phonological balance in the list. Entropy of phonemes in a word is maximized, providing an optimal balance in each word’s phonological distribution using the Add-Delete Method (PBW algorithm) and is compared to the modified PBW algorithm implemented in a dynamic algorithm approach to obtain optimization. The gained entropy score of 4.2791 and 4.2902 for the PBW and modified algorithm respectively. The PBW250 was recorded by 40 respondents, each with 2 sets data. Recordings from 30 respondents were trained to produce an acoustic model that were tested using recordings from 10 respondents using the HMM Toolkit (HTK). The results of test gave the maximum accuracy rate of 97.77% for a speaker dependent test and 89.36% for a speaker independent test.

Keywords: entropy maximization, Filipino language, Hidden Markov Model, phonetically balanced words, speech recognition

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Authors: Christina Roman, Deepak Koirala, Joseph A. Piccirilli

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Phage displaying synthetic Fab libraries have been used to obtain Fabs that bind to specific RNA targets with high affinity and specificity. These Fabs have been demonstrated to facilitate RNA crystallization. However, the antibody framework used in the construction of these phage display libraries contains numerous bulky, flexible, and charged residues, which facilitate solubility and hinder aggregation. These residues can interfere with crystallization due to the entropic cost associated with burying them within crystal contacts. To systematically reduce the surface entropy of the Fabs and improve their crystallization properties, a protein engineering strategy termed surface entropy reduction (SER) is being applied to the Fab framework. In this approach, high entropy residues are mutated to smaller ones such as alanine or serine. Focusing initially on Fab BL3-6, which binds an RNA AAACA pentaloop with 20nM affinity, the SER P server (http://services.mbi.ucla.edu/SER/) was used and analysis was performed on existing RNA-Fab BL3-6 co-crystal structures. From this analysis twelve surface entropy reduced mutants were designed. These SER mutants were expressed and are now being measured for their crystallization and diffraction performance with various RNA targets. So far, one mutant has generated 3.02 angstrom diffraction with the yjdF riboswitch RNA. Ultimately, the most productive mutations will be combined into a new Fab framework to be used in a optimized phage displayed Fab library.

Keywords: antibody fragment, crystallography, RNA, surface entropy reduction

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Authors: Atrin Barzegar, Yas Barzegar, Stefano Marrone, Francesco Bellini, Laura Verde

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The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

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Authors: Michael Gidey Gebru

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Most DEA models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp DEA into DEA with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the DEA model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units’ efficiency. Finally, the developed DEA model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, DEA, fuzzy, decision making units, higher education institutions

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Authors: Joseph Siani

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Over the last decades, dissatisfaction with global indicators of economic performance, such as GDP (Gross Domestic Product) per capita, has shifted the attention to what is now referred to as multidimensional poverty. In this framework, poverty goes beyond income to incorporate aspects of well-being not captured by income measures alone. This paper applies the totally fuzzy approach to estimate the fuzzy index of poverty (FIP) in fourteen Sub-Saharan African (SSA) countries using Demographic and Health Survey (DHS) data and explores whether pictures created by the standard headcount ratio at $1.90 a day and the fuzzy index of poverty tell a similar story. The results suggest that there is indeed considerable mismatch between poverty headcount and the fuzzy index of multidimensional poverty, meaning that the majority of the most deprived people (as identified by the fuzzy index of multidimensional poverty) would not be identified by the poverty headcount ratio. Moreover, we find that poverty is distributed differently by colonial heritage (language). In particular, the most deprived countries in SSA are French-speaking.

Keywords: fuzzy set approach, multidimensional poverty, poverty headcount, overlap, Sub-Saharan Africa

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Authors: Mohamed Amine Haraoubia, Abdelaziz Hamzaoui, Najib Essounbouli

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The pursuit of the MPPT has led to the development of many kinds of controllers, one of which is the Fuzzy Logic Controller, which has proven its worth. To further tune this controller this paper will discuss and analyze the use of Genetic Algorithms to tune the Fuzzy Logic Controller. It will provide an introduction to both systems, and test their compatibility and performance.

Keywords: fuzzy logic controller, fuzzy logic, genetic algorithm, maximum power point, maximum power point tracking

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Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: automatic design, learning, fuzzy rules, hybrid, swarm optimization

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Authors: Saumya R. Jha, Krishanu Biswas, Nilesh P. Gurao

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Several recent investigations have revealed medium entropy alloys exhibiting better mechanical properties than their high entropy counterparts. This clearly establishes that although a higher entropy plays a vital role in stabilization of particular phase over complex intermetallic phases, configurational entropy is not the primary factor responsible for the high inherent strengthening in these systems. Above and beyond a high contribution from friction stresses and solid solution strengthening, strain hardening is an important contributor to the strengthening in these systems. In this regard, researchers have developed severe plastic deformation (SPD) techniques like High Pressure Torsion (HPT) to incorporate very high shear strain in the material, thereby leading to ultrafine grained (UFG) microstructures, which cause manifold increase in the strength. The presented work demonstrates a meticulous study of the variation in mechanical properties at different radial displacements from the center of HPT tested equiatomic ternary FeMnNi synthesized by casting route, which is a low stacking fault energy FCC alloy that shows significantly higher toughness than its high entropy counterparts like Cantor alloy. The gradient in grain sizes along the radial direction of these specimens has been modeled using microstructure entropy for predicting the mechanical properties, which has also been validated by indentation tests. The dislocation density is computed by FEM simulations for varying strains and validated by analyzing synchrotron diffraction data. Thus, the proposed model can be utilized to predict the strengthening behavior of similar systems deformed by HPT subjected to varying loading conditions.

Keywords: high pressure torsion, severe plastic deformation, configurational entropy, dislocation density, FEM simulation

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Authors: Khaled Mammar

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This paper presents an application of adaptive neuro-fuzzy controller for PEM fuel cell system. The model proposed for control include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore, a Fuzzy Logic (FLC) and adaptive neuro-fuzzy controllers are used to control the active power of PEM fuel cell system. The controllers modify the hydrogen flow feedback from the terminal load. The validity of the controller is verified when the fuel cell system model is used in conjunction with the ANFIS controller to predict the response of the active power. Simulation results confirmed the high-performance capability of the neuo-fuzzy to control power generation.

Keywords: fuel cell, PEMFC, modeling, simulation, Fuzzy Logic Controller, FLC, adaptive neuro-fuzzy controller, ANFIS

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Authors: Mujde Turkkan, Nurkan Yagiz

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In this study an active controller is presented for vibration suppression of a full-bus model. The bus is modelled having seven degrees of freedom. Using the achieved model via Lagrange Equations the system equations of motion are derived. The suspensions of the bus model include air springs with two auxiliary chambers are used. Fuzzy logic controller is used to improve the ride comfort. The numerical results, verifies that the presented fuzzy logic controller improves the ride comfort.

Keywords: ride comfort, air spring, bus, fuzzy logic controller

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Authors: Omar M. Aldenali

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Planning is one of the most important phases of the management science and network planning, which represents the project activities relationship. Critical path is one of the project management techniques used to plan and control the execution of a project activities. The objective of this paper is to implement a fuzzy logic approach to arrange network planning on construction projects. This method is used to finding out critical path in the fuzzy construction project network. The trapezoidal fuzzy numbers are used to represent the activity construction project times. A numerical example that represents a house construction project is introduced. The critical path method is implemented on the fuzzy construction network activities, and the results showed that this method significantly affects the completion time of the construction projects.

Keywords: construction project, critical path, fuzzy network project, planning

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Authors: Reginaldo Cardoso, Magno Enrique Mendoza Meza

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This work focuses on simulation and comparison of two control skyhook techniques applied to a quarter-car of the active suspension. The objective is to provide comfort to the driver. The main idea of skyhook control is to imagine a damper connected to an imaginary sky; thus, the feedback is performed with the resultant force between the imaginary and the suspension damper. The first control technique is the Mandani fuzzy skyhook and the second control technique is a Takagi-Sugeno fuzzy skyhook controller, in the both controllers the inputs are the relative velocity between the two masses and the vehicle body velocity, the output of the Mandani fuzzy skyhook is the coefficient of imaginary damper viscous-friction and the Takagi-Sugeno fuzzy skyhook is the force. Finally, we compared the techniques. The Mandani fuzzy skyhook showed a more comfortable response to the driver, followed closely by the Takagi- Sugeno fuzzy skyhook.

Keywords: active suspention, Mandani, quarter-car, skyhook, Sugeno

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Authors: Bessaad Taieb, Benbouali Abderrahmen

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Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller.

Keywords: fuzzy adaptive control, behaviour model control, vector control, five-phase asynchronous machine

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Authors: Jiaxin Chen

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Translations have been labeled as more simplified than non-translations, featuring less diversified and more frequent lexical items and simpler syntactic structures. Such simplified linguistic features have been identified in other bilingualism-influenced language varieties, including non-native and learner language use. Therefore, it has been proposed that translation could be studied within a broader framework of constrained language, and simplification is one of the universal features shared by constrained language varieties due to similar cognitive-physiological and social-interactive constraints. Yet contradicting findings have also been presented. To address this issue, this study intends to adopt Shannon’s entropy-based measures to quantify complexity in language use. Entropy measures the level of uncertainty or unpredictability in message content, and it has been adapted in linguistic studies to quantify linguistic variance, including morphological diversity and lexical richness. In this study, the complexity of lexical and syntactic choices will be captured by word-form entropy and pos-form entropy, and a comparison will be made between constrained and non-constrained language use to test the simplification hypothesis. The entropy-based method is employed because it captures both the frequency of linguistic choices and their evenness of distribution, which are unavailable when using traditional indices. Another advantage of the entropy-based measure is that it is reasonably stable across languages and thus allows for a reliable comparison among studies on different language pairs. In terms of the data for the present study, one established (CLOB) and two self-compiled corpora will be used to represent native written English and two constrained varieties (L2 written English and translated English), respectively. Each corpus consists of around 200,000 tokens. Genre (press) and text length (around 2,000 words per text) are comparable across corpora. More specifically, word-form entropy and pos-form entropy will be calculated as indicators of lexical and syntactical complexity, and ANOVA tests will be conducted to explore if there is any corpora effect. It is hypothesized that both L2 written English and translated English have lower entropy compared to non-constrained written English. The similarities and divergences between the two constrained varieties may provide indications of the constraints shared by and peculiar to each variety.

Keywords: constrained language use, entropy-based measures, lexical simplification, syntactical simplification

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Authors: R. Mellah, R. Toumi

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This paper presents a new adaptive neuro-fuzzy controller equipped with compensatory fuzzy control (CNFI) in order to not only adjusts membership functions but also to optimize the adaptive reasoning by using a compensatory learning algorithm. The proposed control structure includes both CNFI controllers for which one is used to control in force the master robot and the second one for controlling in position the slave robot. The experimental results obtained, show a fairly high accuracy in terms of position and force tracking under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers.

Keywords: compensatory fuzzy, neuro-fuzzy, control adaptive, teleoperation

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Authors: Syed Ahzam Tariq, Atharva Modi

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This paper presents a probabilistic analysis of the safety of water tube boilers using fault tree analysis (FTA). A fault tree has been constructed by considering all possible areas where a malfunction could lead to a boiler accident. Boiler accidents are relatively rare, causing a scarcity of data. The fuzzy approach is employed to perform a quantitative analysis, wherein theories of fuzzy logic are employed in conjunction with expert elicitation to calculate failure probabilities. The Fuzzy Fault Tree Analysis (FFTA) provides a scientific and contingent method to forecast and prevent accidents.

Keywords: fault tree analysis water tube boiler, fuzzy probability score, failure probability

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Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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Authors: Seungwoo Kim, Yeongcheol Cho

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In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task.

Keywords: fuzzy adaptive control, fuzzy multi-layered controller, holonomic mobile robot, omnidirectional wheels, robustness and stability.

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Authors: Muhammad M. A. S. Mahmoud

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Natural gas sweetening process is a controlled process that must be done at maximum efficiency and with the highest quality. In this work, due to complexity and non-linearity of the process, the H₂S gas separation and the intelligent fuzzy controller, which is used to enhance the process, are simulated in MATLAB – Simulink. The new design of fuzzy control for Gas Separator is discussed in this paper. The design is based on the utilization of linear state-estimation to generate the internal knowledge-base that stores input-output pairs. The obtained input/output pairs are then used to design a feedback fuzzy controller. The proposed closed-loop fuzzy control system maintains the system asymptotically-stability while it enhances the system time response to achieve better control of the concentration of the output gas from the tower. Simulation studies are carried out to illustrate the Gas Separator system performance.

Keywords: gas separator, gas sweetening, intelligent controller, fuzzy control

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Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng

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The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.

Keywords: electro-rheological fluid, semi-active vibration control, shock absorber, type 2 fuzzy control

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Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

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Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design.

Keywords: information entropy, structural optimization, truss structure, whale algorithm

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Authors: R. Rama Kishore, Sunesh

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This paper presents an optimized, robust, and secured watermarking technique. The methodology used in this work is the combination of entropy and chaotic grid map. The proposed methodology incorporates Discrete Cosine Transform (DCT) on the host image. To improve the imperceptibility of the method, the host image DCT blocks, where the watermark is to be embedded, are further optimized by considering the entropy of the blocks. Chaotic grid is used as a key to reorder the DCT blocks so that it will further increase security while selecting the watermark embedding locations and its sequence. Without a key, one cannot reveal the exact watermark from the watermarked image. The proposed method is implemented on four different images. It is concluded that the proposed method is giving better results in terms of imperceptibility measured through PSNR and found to be above 50. In order to prove the effectiveness of the method, the performance analysis is done after implementing different attacks on the watermarked images. It is found that the methodology is very strong against JPEG compression attack even with the quality parameter up to 15. The experimental results are confirming that the combination of entropy and chaotic grid map method is strong and secured to different image processing attacks.

Keywords: digital watermarking, discreate cosine transform, chaotic grid map, entropy

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Authors: Mohammad Sarchami, Mohsen Zeinalkhani

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Always, financial reporting system faces some problems to win public ear. The increase in the number of fraud and representation, often combined with the bankruptcy of large companies, has raised concerns about the quality of financial statements. So, investors, legislators, managers, and auditors have focused on significant fraud detection or prevention in financial statements. This article aims to investigate the Sugeno fuzzy classification to consider fraud detection in financial reporting of accepted firms by Tehran stock exchange. The hypothesis is: Sugeno fuzzy classification may detect fraud in financial reporting by financial ratio. Hypothesis was tested using Matlab software. Accuracy average was 81/80 in Sugeno fuzzy classification; so the hypothesis was confirmed.

Keywords: fraud, financial reporting, Sugeno fuzzy classification, firm

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Authors: Guoliang Fan, Aiping Li, Xuemei Liu, Liyun Xu

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The performance of the tightening equipment will decline with the working process in manufacturing system. The main manifestations are the randomness and discretization degree increasing of the tightening performance. To evaluate the degradation tendency of the tightening performance accurately, a complexity measurement approach based on Kolmogorov entropy is presented. At first, the states of performance index are divided for calibrating the discrete degree. Then the complexity measurement model based on Kolmogorov entropy is built. The model describes the performance degradation tendency of tightening equipment quantitatively. At last, a study case is applied for verifying the efficiency and validity of the approach. The research achievement shows that the presented complexity measurement can effectively evaluate the degradation tendency of the tightening equipment. It can provide theoretical basis for preventive maintenance and life prediction of equipment.

Keywords: complexity measurement, Kolmogorov entropy, manufacturing system, performance evaluation, tightening equipment

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Authors: Aquil Ahmed, Srikant Gupta, Irfan Ali

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In this paper, we study a multi-objective capacitated transportation problem (MOCTP) with mixed constraints. This paper is comprised of the modelling and optimisation of an MOCTP in a fuzzy environment in which some goals are fractional and some are linear. In real life application of the fuzzy goal programming (FGP) problem with multiple objectives, it is difficult for the decision maker(s) to determine the goal value of each objective precisely as the goal values are imprecise or uncertain. Also, we developed the concept of linearization of fractional goal for solving the MOCTP. In this paper, imprecision of the parameter is handled by the concept of fuzzy set theory by considering these parameters as a trapezoidal fuzzy number. α-cut approach is used to get the crisp value of the parameters. Numerical examples are used to illustrate the method for solving MOCTP.

Keywords: capacitated transportation problem, multi objective linear programming, multi-objective fractional programming, fuzzy goal programming, fuzzy sets, trapezoidal fuzzy number

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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