Search results for: fuzzy numbers

Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.

Keywords: DSEP, fuzzy logic, energy model, WSN

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Authors: Abbas Al-Refaie

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This study optimized the performance of plastic extrusion process of drip irrigation pipes using fuzzy goal programming. Two main responses were of main interest; roll thickness and hardness. Four main process factors were studied. The L₁₈ array was then used for experimental design. The individual-moving range control charts were used to assess the stability of the process, while the process capability index was used to assess process performance. Confirmation experiments were conducted at the obtained combination of optimal factor setting by fuzzy goal programming. The results revealed that process capability was improved significantly from -1.129 to 0.8148 for roll thickness and from 0.0965 to 0.714 and hardness. Such improvement results in considerable savings in production and quality costs.

Keywords: fuzzy goal programming, extrusion process, process capability, irrigation plastic pipes

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Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

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Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic

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Authors: E. A. Tkachenko, E. M. Rogova, V. V. Klimov

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One of the basic issues of development management is connected with performance measurement as a prerequisite for identifying the achievement of development objectives. The aim of our research is to develop an improved model of assessing a company’s development results. The model should take into account the cyclical nature of development and the high degree of uncertainty in dealing with numerous management tasks. Our hypotheses may be formulated as follows: Hypothesis 1. The cycle of a company’s development may be studied from the standpoint of a project cycle. To do that, methods and tools of project analysis are to be used. Hypothesis 2. The problem of the uncertainty when justifying managerial decisions within the framework of a company’s development cycle can be solved through the use of the mathematical apparatus of fuzzy logic. The reasoned justification of the validity of the hypotheses made is given in the suggested article. The fuzzy logic toolkit applies to the case of technology shift within an enterprise. It is proven that some restrictions in performance measurement that are incurred to conventional methods could be eliminated by implementation of the fuzzy logic apparatus in performance measurement models.

Keywords: logic, fuzzy sets, performance measurement, project analysis

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Authors: Xiangchun Wang, Lihui Zheng, Maozong Gan, Peng Zhang, Tong Wu, An Chang

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The deep coal measure tight gas reservoir in Sulige is usually reformed by fracturing, because the reservoir thickness is small, the water layers can be easily communicated during fracturing, which will lead to water production of gas wells and lower production of gas wells. Therefore, it is necessary to control water during fracturing in deep coal measure tight gas reservoir. Using fuzzy-ball fluid to control water fracturing can not only increase the output but also reduce the water output. The fuzzy-ball fluid was prepared indoors to carry out evaluation experiments. The fuzzy ball fluid was mixed in equal volume with the pre-fluid and formation water to test its compatibility. The core displacement device was used to test the gas and water breaking through the matrix and fractured cores blocked by fuzzy-ball fluid. The breakthrough pressure of the plunger tests its water blocking performance. The experimental results show that there is no precipitation after the fuzzy-ball fluid is mixed with the pad fluid and the formation water, respectively. The breakthrough pressure gradients of gas and water after the fuzzy-ball fluid plugged the cracks were 0.02MPa/cm and 0.04MPa/cm, respectively, and the breakthrough pressure gradients of gas and water after the matrix was plugged were 0.03MPa/cm and 0.2MPa/cm, respectively, which meet the requirements of field operation. Two wells A and B in the Sulige Gas Field were used on site to implement water control fracturing. After the pre-fluid was injected into the two wells, 50m3 of fuzzy-ball fluid was pumped to plug the water. The construction went smoothly. After water control and fracturing, the average daily output in 161 days was increased by 13.71% and 6.99% compared with that of adjacent wells in the same layer. The adjacent wells were bubbled for 3 times and 63 times respectively, while there was no effusion in A and B construction wells. The results show that fuzzy-ball fluid is a water plugging material suitable for water control fracturing in tight gas wells, and its water control mechanism can also provide a new idea for the development of water control fracturing materials.

Keywords: coal seam, deep layer, fracking, fuzzy-ball fluid, reservoir reconstruction

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Authors: Jalal Abdulkareem Sultan, Abdulhakeem Luqman Hasan

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With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use.

Keywords: bed allocation problem, fuzzy logic, artificial bee colony, multi-objective optimization

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Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

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Authors: Hamidreza Fallah Lajimi , Elham Karami, Fatemeh Ali nasab, Mostafa Mahdavikia

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Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering

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Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou

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The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.

Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval

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Authors: Kim Michelle Siegling, Thomas Spengler, Sebastian Herzog

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In personnel economics, the choice of a leadership style is about the question of how a supervisor should lead his or her employees in such a way that operational goals are achieved. In this paper, it is assumed that such leadership decisions are made according to the situation. Thus, the optimal or at least a permissible leadership style has to be selected from a set of several possible leadership styles. For this choice, a wide range of models has been developed in the scientific literature, from which the so-called normative decision model will be picked out and focused on. While the original model is based on univocal rules, this paper develops a fuzzy rule system.

Keywords: leadership, leadership styles, rule based systems, fuzzy logic

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Tanveer Rasool, A. K. Dhiman

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The paper reports 2-D numerical study used to investigate the effect of changing working fluids with Prandtl numbers 0.71, 10 and 50 on the flow and convective heat transfer across an equilateral triangular cylinder placed in a horizontal channel with its apex facing the flow. Numerical results have been generated for fixed blockage ratio of 50% and for three Reynolds numbers of 50, 75, and 100 for each Prandtl numbers respectively. The studies show that for above range of Reynolds numbers, the overall drag coefficient is insensitive to the Prandtl number changes while as the heat transfer characteristics change drastically with changing Prandtl number of the working fluid. The results generated are in complete agreement with the previous literature available.

Keywords: Prandtl number, Reynolds number, drag coefficient, flow and isothermal patterns

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Authors: Jinming Ma, Tianbing Xia, Janusz Getta

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This paper presents the application of fuzzy set theory to implement of mobile advertisement anti-fraud systems. Mobile anti-fraud is a method aiming to identify mobile advertisement fraudsters. One of the main problems of mobile anti-fraud is the lack of evidence to prove a user to be a fraudster. In this paper, we implement an application by using fuzzy set theory to demonstrate how to detect cheaters. The advantage of our method is that the hardship in detecting fraudsters in small data samples has been avoided. We achieved this by giving each user a suspicious degree showing how likely the user is cheating and decide whether a group of users (like all users of a certain APP) together to be fraudsters according to the average suspicious degree. This makes the process more accurate as the data of a single user is too small to be predictable.

Keywords: mobile internet, advertisement, anti-fraud, fuzzy set theory

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Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

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Authors: Morteza Khorrami

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The logic as an intellectual infrastructure plays an essential role in the Islamic sciences. Hence, there are a few of the verses of the Holy Quran that their interpretation is not possible due to lack of proper logic. In many verses in the Quran, argument and the respondent has requested from the audience that shows the logic rule is in the Quran. The paper which use a descriptive and analytic method, tries to show the role of logic in understanding of the Quran reasoning methods and display some of Quranic statements with mathematical symbols and point that we can help these symbols for interesting and interpretation and answering to some questions and doubts. In this paper, this problem has been mentioned that the Quran did not use two-valued logic (Aristotelian) in all cases, but the fuzzy logic can also be searched in the Quran.

Keywords: aristotelian logic, fuzzy logic, interpretation, Holy Quran

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Authors: X. L. Nguyen, T. Y. Chou, F. Y. Min, F. C. Lin, T. V. Hoang, Y. M. Huang

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In Vietnam, land use planning is utilized as an efficient tool for the local government to adjust land use. However, planned locations are facing disapproval from people who live near these planned sites because of environmental problems. The selection of these locations is normally based on the subjective opinion of decision-makers and is not supported by any scientific methods. Many researchers have applied Multi-Criteria Analysis (MCA) methods in which Analytic Hierarchy Process (AHP) is the most popular techniques in combination with Fuzzy set theory for the subject of rationality assessment of land use planning locations. In this research, the Fuzzy set theory and Analytic Network Process (ANP) multi-criteria-based technique were used for the assessment process. The Fuzzy Analytic Hierarchy Process was also utilized, and the output results from two methods were compared to extract the differences. The 20 planned landfills in Hung Ha district, Thai Binh province, Vietnam was selected as a case study. The comparison results indicate that there are different between weights computed by AHP and ANP methods and the assessment outputs produced from these two methods also slight differences. After evaluation of existing planned sites, some potential locations were suggested to the local government for possibility of land use planning adjusts.

Keywords: Analytic Hierarchy Process, Analytic Network Process, Fuzzy set theory, land use planning

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Authors: Nicolás Rudas

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Sociologists have brought to light the fascination of contemporary societies with numbers but fall short of explaining it. In their accounts, people generally misunderstand the technical intricacies of statistical knowledge and therefore accept numbers as unassailable “facts”. It is due to such pervasive fascination, furthermore, that both old and new forms of social control find fertile ground. By focusing on the process whereby the fetishization of numbers reaches its zenith, i.e., when specific statistics become emblematic of an entire society, it is asserted that numbers primarily function as moral symbols with immense potential for galvanizing collective action. Their “facticity” is not solely a cognitive problem but one that is deeply rooted in myth and connected with social experiences of epiphany and ritual. Evidence from Colombia is used to illustrate how certain quantifications become canonical. In 2021, Colombia’s Peace Court revealed that the national army had executed 6,402 innocent civilians to later report them as members of illegal armed groups. Rapidly, “6,402” transformed into a prominent item in the country’s political landscape. This article reconstructs such a process by following the first six months of the figure’s circulation, both in traditional and social media. In doing so, it is developed a new cultural-sociological conceptualization of numbers as “fact-icons” that departs from traditional understandings of statistics as “technical” objects. Numbers are icons whose appropriation is less rational than aesthetic.

Keywords: culture, statistics, collective memory, social movements

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Authors: E. Rama Devi Jothilingam

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Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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Authors: Hamidreza Fallah Lajimi, Elham Karami, Alireza Arab, Fatemeh Alinasab

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Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with Four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering, business engineering

Procedia PDF Downloads 712

Authors: Mahdi Alshamasin, Riad Al-Kasasbeh, Nikolay Korenevskiy

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We apply mathematical models for the interaction of the internal and biologically active points of meridian structures. Amongst the diseases for which reflex diagnostics are effective are those of the stomach disease. It is shown that use of fuzzy logic decision-making yields good results for the prediction and early diagnosis of gastrointestinal tract diseases, depending on the reaction energy of biologically active points (acupuncture points). It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained by using fuzzy logic decision-making.

Keywords: acupuncture points, fuzzy logic, diagnostically important points (DIP), confidence factors, membership functions, stomach diseases

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Authors: Nadama Kumar, P. Parthiban, T. Niranjan

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In the present paper, we propose an incorporated approach for 3PL supplier choice that suits the distinctive strategic needs of the outsourcing organization in southern part of India. Four fundamental criteria have been used in particular Performance, IT, Service and Intangible. These are additionally subdivided into fifteen sub-criteria. The proposed strategy coordinates Structural Equation Modeling (SEM) and Non-additive Fuzzy Integral strategies. The presentation of fluffiness manages the unclearness of human judgments. The SEM approach has been used to approve the determination criteria for the proposed show though the Non-additive Fuzzy Integral approach uses the SEM display contribution to assess a supplier choice score. The case organization has a exclusive vertically integrated assembly that comprises of several companies focusing on a slight array of the value chain. To confirm manufacturing and logistics proficiency, it significantly relies on 3PL suppliers to attain supply chain superiority. However, 3PL supplier selection is an intricate decision-making procedure relating multiple selection criteria. The goal of this work is to recognize the crucial 3PL selection criteria by using the non-additive fuzzy integral approach. Unlike the outmoded multi criterion decision-making (MCDM) methods which frequently undertake independence among criteria and additive importance weights, the nonadditive fuzzy integral is an effective method to resolve the dependency among criteria, vague information, and vital fuzziness of human judgment. In this work, we validate an empirical case that engages the nonadditive fuzzy integral to assess the importance weight of selection criteria and indicate the most suitable 3PL supplier.

Keywords: 3PL, non-additive fuzzy integral approach, SEM, fuzzy

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Authors: Busaba Phurksaphanrat

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This research proposes a pre-emptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of make-span. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, pre-emptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions.

Keywords: multi-mode resource constrained project scheduling problem, fuzzy set, goal programming, pre-emptive fuzzy goal programming

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Authors: David G. Maxinez, Andrés Ferreyra Ramírez, Liliana Castillo Sánchez, Nancy Adán Mendoza, Carlos Aviles Cruz

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This research describes the use of fuzzy logic in detection, assessment, analysis and evaluation of children with behavioral disorders. It shows how to acquire and analyze ambiguous, vague and full of uncertainty data coming from the input variables to get an accurate assessment result for each of the typologies presented by children with behavior problems. Behavior disorders analyzed in this paper are: hyperactivity (H), attention deficit with hyperactivity (DAH), conduct disorder (TD) and attention deficit (AD).

Keywords: alteration, behavior, centroid, detection, disorders, economic, fuzzy logic, hyperactivity, impulsivity, social

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Authors: E. Mike Dison, T. Pathinathan

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Computing with Words (CWW) and Possibilistic Relational Universal Fuzzy (PRUF) are the two concepts which widely represent and measure the vaguely defined natural phenomenon. In this paper, we study the positional alteration of the phrases by which the impact of a natural language proposition gets affected and/or modified. We observe the gradations due to sensitivity/feeling of a statement towards the positional alterations. We derive the classification and modification of the meaning of words due to the positional alteration. We present the results with reference to set theoretic interpretations.

Keywords: appositive, computing with words, possibilistic relational universal fuzzy (PRUF), semantic sentiment analysis, set-theoretic interpretations

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Authors: U. Chattaraj, D. Meena

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Growth of traffic brings various negative effects, such as road accidents. To avoid such problems, a model is developed for the purpose of highway safety. In such areas, fuzzy logic is the most well-known simulation in the larger field. A model is accomplished for hilly and steep terrain based on Fuzzy Inference System (FIS), for which output is super elevation and input data is horizontal radius, vertical gradient, accident rate (AR). This result shows that the system can be efficaciously applied as for highway safety tool distinguishing hazards components correlated to the characteristics of the highway and has a great influence to the making of decision for accident precaution in transportation models. From this model, a positive relationship between geometric elements, accident rate, and super elevation is also identified.

Keywords: accident rate, fuzzy inference system, fuzzy logic, gradient, radius, super elevation

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Authors: Alireza Gholami, Amir H. D. Markazi

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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: adaptive algorithm, fuzzy systems, membership functions, observer

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Authors: Thierry Ganomanana, Dominique Hervé, Solo Randriamahaleo

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Management of Malagasy renewable natural re-sources allows, in the case of forest, the mobilization of several actors with norms and/or territory. The interaction in this socio-ecosystem is represented by a graph of two different relationships in which most of action chains, from individual activities under the continuous of forest dynamic and discrete interventions by institutional, are also studied. The fuzzy set theory is adapted to graduate the elements of the set Illegal Activities in the space of sanction’s institution by his severity and in the space of degradation of forest by his extent.

Keywords: fuzzy set, graph, institution, renewable resource, system

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Authors: Nafiseh Mollaei, Reihaneh Kardehi Moghaddam

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In case of Diabetes Mellitus the controlling of insulin is very difficult. This illness is an incurable disease affecting millions of people worldwide. Glucose is a sugar which provides energy to the cells. Insulin is a hormone which supports the absorption of glucose. Fuzzy control strategy is attractive for glucose control because it mimics the first and second phase responses that the pancreas beta cells use to control glucose. We propose two control algorithms a type-1 fuzzy controller and an interval type-2 fuzzy method for the insulin infusion. The closed loop system has been simulated for different patients with different parameters, in present of the food intake disturbance and it has been shown that the blood glucose concentrations at a normoglycemic level of 110 mg/dl in the reasonable amount of time. This paper deals with type 1 diabetes as a nonlinear model, which has been simulated in MATLAB-SIMULINK environment. The novel model, termed the Augmented Minimal Model is used in the simulations. There are some uncertainties in this model due to factors such as blood glucose, daily meals or sudden stress. In addition to eliminate the effects of uncertainty, different control methods may be utilized. In this article, fuzzy controller performance were assessed in terms of its ability to track a normoglycemic set point (110 mg/dl) in response to a [0-10] g meal disturbance. Finally, the development reported in this paper is supposed to simplify the insulin delivery, so increasing the quality of life of the patient.

Keywords: interval type-2, fuzzy controller, minimal augmented model, uncertainty

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Authors: Sahar Maâlej Dammak, Anis Jedidi, Rafik Bouaziz

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With the great mass of pages managed through the world, and especially with the advent of the Web, their manual annotation is impossible. We focus, in this paper, on the semiautomatic annotation of the web pages. We propose an approach and a framework for semantic annotation of web pages entitled “Querying Web”. Our solution is an enhancement of the first result of annotation done by the “Semantic Radar” Plug-in on the web resources, by annotations using an enriched domain ontology. The concepts of the result of Semantic Radar may be connected to several terms of the ontology, but connections may be uncertain. We represent annotations as possibility distributions. We use the hierarchy defined in the ontology to compute degrees of possibilities. We want to achieve an automation of the fuzzy semantic annotation of web resources.

Keywords: fuzzy semantic annotation, semantic web, domain ontologies, querying web

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Authors: Mahesh Kothari, K. D. Gharde

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The ANN and fuzzy logic (FL) models were developed to predict the runoff and sediment yield for catchment of Kal river, India using 21 years (1991 to 2011) rainfall and other hydrological data (evaporation, temperature and streamflow lag by one and two day) and 7 years data for sediment yield modelling. The ANN model performance improved with increasing the input vectors. The fuzzy logic model was performing with R value more than 0.95 during developmental stage and validation stage. The comparatively FL model found to be performing well to ANN in prediction of runoff and sediment yield for Kal river.

Keywords: transferred function, sigmoid, backpropagation, membership function, defuzzification

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