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Advanced Fuzzy Logic Approaches in Engineering Science最新文献

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Fuzzy Sumudu Transform Approach to Solving Fuzzy Differential Equations With Z-Numbers 求解z数模糊微分方程的模糊Sumudu变换方法
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 2018-09-01 DOI: 10.4018/978-1-5225-5709-8.CH002
R. Jafari, S. Razvarz, A. Gegov, Satyam Paul, S. Keshtkar
{"title":"Fuzzy Sumudu Transform Approach to Solving Fuzzy Differential Equations With Z-Numbers","authors":"R. Jafari, S. Razvarz, A. Gegov, Satyam Paul, S. Keshtkar","doi":"10.4018/978-1-5225-5709-8.CH002","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH002","url":null,"abstract":"Uncertain nonlinear systems can be modeled with fuzzy differential equations (FDEs) and the solutions of these equations are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs. In this book chapter, the solutions of FDEs are approximated by utilizing the fuzzy Sumudu transform (FST) method. Here, the uncertainties are in the sense of fuzzy numbers and Z-numbers. Important theorems are laid down to illustrate the properties of FST. This new technique is compared with Average Euler method and Max-Min Euler method. The theoretical analysis and simulation results show that the FST method is effective in estimating the solutions of FDEs.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123409362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
Fuzzy-Probability 种模糊
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH009
P. Dutta
{"title":"Fuzzy-Probability","authors":"P. Dutta","doi":"10.4018/978-1-5225-5709-8.CH009","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH009","url":null,"abstract":"Human health risk assessment is an important and a popular aid in the decision-making process. The basic objective of risk assessment is to assess the severity and likelihood of impairment to human health from exposure to a substance or activity that under plausible circumstances can cause harm to human health. One of the most important aspects of risk assessment is to accumulate knowledge on the features of each and every available data, information and model parameters involved in risk assessment. It is observed that most frequently model parameters, data, and information are tainted with aleatory and epistemic uncertainty. In such situations, fuzzy set theory or probability theory or Dempster-Shafer theory (DSS) can be explored to represent uncertainty. If all the three types of uncertainty coexist how far computation of the risk is concern, two ways to deal with the situation either transform all the uncertainties to one type of format or need for joint propagation of uncertainties. Therefore, this article presents an effort to combine Probability distributions, fuzzy numbers (FNs) and DSS. Highlights of this study are: 1) The approaches presented here deal with the amalgamation of probability distributions where representations of parameters are of bell shaped fuzzy numbers (BFNs)/FNs; fuzzy numbers (FNs) of various types and shapes plus DSS with fuzzy focal elements of different types within the same framework; 2) Non-cancer human health risk assessment is carried out in this setting and 3) Risk values are obtained in the form of FNs at different fractiles. The techniques provided in this study are proficient to exploit in any mathematical models which represent real world problems, wherein model parameters are tainted with uncertainty where representations of uncertain model parameters are probability distributions with bell BFNs/FNs parameters; DSS with fuzzy focal elements of different types plus FNs with different shapes and types.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122381063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reliability Analysis for Environment Systems Using Dual Hesitant Fuzzy Set 基于对偶犹豫模糊集的环境系统可靠性分析
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH008
Akshay Kumar, M. Ram
{"title":"Reliability Analysis for Environment Systems Using Dual Hesitant Fuzzy Set","authors":"Akshay Kumar, M. Ram","doi":"10.4018/978-1-5225-5709-8.CH008","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH008","url":null,"abstract":"In this chapter, we deal with dual hesitant fuzzy set theory and compute the fuzzy reliability with lifetime components of different electronic systems, such as series and parallel systems from a Markov chain technique. In dual hesitant fuzzy sets, we have membership and non-membership degree function whereas hesitant fuzzy sets only have membership function. In this chapter we also discuss the Weibull distribution and reliability function of the proposed systems. A numerical example is also given in the end of proposed algorithm.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125254319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
A Study and Estimation of Different Distance Measures in Generalized Fuzzy TOPSIS to Improve Ranking Order 广义模糊TOPSIS中不同距离测度改进排序的研究与估计
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH010
Martin Aruldoss, Miranda Lakshmi Travis, Prasanna Venkatesan Venkatasamy
{"title":"A Study and Estimation of Different Distance Measures in Generalized Fuzzy TOPSIS to Improve Ranking Order","authors":"Martin Aruldoss, Miranda Lakshmi Travis, Prasanna Venkatesan Venkatasamy","doi":"10.4018/978-1-5225-5709-8.CH010","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH010","url":null,"abstract":"Multi criteria decision making (MCDM) is used to solve multiple conflicting criteria. There are different methods available in MCDM out of which TOPSIS is a well- known method to solve precise and imprecise information. In this chapter, triangular fuzzy TOPSIS is considered which has different steps like normalization, weight, finding of positive ideal solution (PIS) and negative ideal solution (NIS), distance between PIS and NIS, calculating relative closeness coefficient (RCC) value and ranking the alternatives. Out of these different steps a distance method is studied. The distance measures are basically used to find the distance between the target alternative and the best and the least alternatives. The most commonly used distance method is Euclidean distance. Many other distance methods are available such as Manhattan, Bit-vector, Hamming, Chebyshev distance, etc. To obtain the appropriate distance, these methods are evaluated. The proposed approach is applied in banking domain to find the suitable user for multi criteria reporting (MCR).","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"456 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132901835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Review of Systems Reliability Analysis Using Fuzzy Logic 基于模糊逻辑的系统可靠性分析综述
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH017
M. Abdolshah, Ali Samavi, Seyyed Amirmohammad Khatibi, Maryam Mamoolraftar
{"title":"A Review of Systems Reliability Analysis Using Fuzzy Logic","authors":"M. Abdolshah, Ali Samavi, Seyyed Amirmohammad Khatibi, Maryam Mamoolraftar","doi":"10.4018/978-1-5225-5709-8.CH017","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH017","url":null,"abstract":"Reliability is one of the important aspects in product quality that shows efficiency or operation of the product, failure rate, and confidence. When the efficiency of the product is reduced below a desired level, the product is said to have failure. In real world, data collection or access of detailed features of the system is often difficult because of incomplete or unavailable information and probabilistic approach to the conventional reliability analysis. Therefore, to solve this problem, fuzzy set theory is used to evaluate system reliability. This research studies the literature on the reliability of fuzzy systems. Several studies have shown that fuzzy logic method can be more appropriate in comparison with classical methods and mathematical modeling.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127768721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Comparative Evaluation of Crisp and Fuzzy Schemes to Solve Chemical Kinetic Models 求解化学动力学模型的清晰和模糊方案的比较评价
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH007
A. Dhaundiyal, S. B. Singh, Muammel M. Hanon
{"title":"Comparative Evaluation of Crisp and Fuzzy Schemes to Solve Chemical Kinetic Models","authors":"A. Dhaundiyal, S. B. Singh, Muammel M. Hanon","doi":"10.4018/978-1-5225-5709-8.CH007","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH007","url":null,"abstract":"This study investigates the application of the crisp and the fuzzy schemes to evaluate the kinetic parameters of thermal decomposition of biomass. A distributed reactivity model is considered for the demonstration of mathematical methods for pyrolysis of biomass. The numerical solution is assessed on the assumption that it follows Laplace's method for asymptotic evaluation of integral. A parabolic regime of temperature is subjected to examination by the thermal analysis. The relevant parameters and variables related to biomass and distribution function are assessed on the basis of crisp and fuzzy perspectives. A distributed reactivity method relies on the modelling of pyrolysis reactions where an overlapping of parallel reactions leads to reactivity distribution, which can be symbolised by any distribution functions. Therefore, the normal distribution pattern is assumed to be involved in the given problem of pyrolysis. The temperature regime is supposed to follow the equation of parabola, T=at^2+c.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128971873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Trajectory Planning and Control Algorithms of Mobile Robots for Static Environments 静态环境下移动机器人的轨迹规划与控制算法
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH018
C. Urrea
{"title":"Trajectory Planning and Control Algorithms of Mobile Robots for Static Environments","authors":"C. Urrea","doi":"10.4018/978-1-5225-5709-8.CH018","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH018","url":null,"abstract":"In this chapter, different types of trajectory control and planning algorithms for mobile robots in static environments are analyzed and assessed. To this end, a mobile robot is made to plan and follow a route between two arbitrary points in an autonomous way. This work goes in depth into the discrete space techniques and those based on search trees. First, kinematics, trajectory planning and contour maps, robot control, etc. are reviewed. Second, computer simulations that validate these theoretical results are also designed and implemented. Finally, the strengths and weaknesses of each trajectory planning methodology are assessed.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126218046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fuzzy Logic Approach for Material Selection in Mechanical Engineering Design 机械工程设计中材料选择的模糊逻辑方法
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH005
N. Faisal, A. Roy, Kaushik Kumar
{"title":"Fuzzy Logic Approach for Material Selection in Mechanical Engineering Design","authors":"N. Faisal, A. Roy, Kaushik Kumar","doi":"10.4018/978-1-5225-5709-8.CH005","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH005","url":null,"abstract":"The selection of materials for a product in mechanical design holds a great importance as the selection of a specific material can impact the success or failure of the product. There are lot of methods and approaches that are available for material selection process, but majority of them work well with only material properties dealing in quantitatively measured properties. With so much amount of material being developed and researched each and every day, the selection of an optimum material has become a fuzzy characteristic. In this chapter, a simplified fuzzy logic is used as a simple, easy and effective method for choosing an optimum material in mechanical design problems. An illustration is carried out when the fuzzy logic is applied to the selection of material for aircraft wing's spar and how an optimum material is achieved.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121496951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design, Comparison, and Evaluation of Controllers for Direct Current Servomotors 直流伺服电机控制器的设计、比较与评估
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH019
C. Urrea, Luis Valenzuela
{"title":"Design, Comparison, and Evaluation of Controllers for Direct Current Servomotors","authors":"C. Urrea, Luis Valenzuela","doi":"10.4018/978-1-5225-5709-8.CH019","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH019","url":null,"abstract":"The results and comparison of controller performance based on fuzzy logic and neural networks with the purpose of improving the performance of PID controllers currently used in servomotors is presented. The performance comparisons will be made with no load and with load (consisting of a robotic type rotational link). The results show that as the number of links in a robot increases, the precision of the movements desired from it decreases, affecting the tasks that require a high degree of precision, so the design of controllers like those presented in this chapter is required. This work is the basis for implementing improvements in the performance of DC servomotor control systems in general.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130293283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Recent Trends and Applications of Fuzzy Logic 模糊逻辑的最新趋势和应用
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH015
P. Srivastava, D. Bisht
{"title":"Recent Trends and Applications of Fuzzy Logic","authors":"P. Srivastava, D. Bisht","doi":"10.4018/978-1-5225-5709-8.CH015","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH015","url":null,"abstract":"Classical set theory, which is based on dichotomy, is not applicable in cases where vagueness is involved. Fuzzy logic is based on the idea of relative graded membership. Fuzzy logic has all the strength to cope with vagueness, uncertainty, and imprecision. Fuzzy logic is a tool that connects human cognitive relations to computers, since computers are not at all good in reading imprecise and vague data. Fuzzy logic is gaining its popularity in various field of research. It found its application in decision making, identification, time series, pattern recognition, optimization, and control. This chapter discusses fuzzy logic, fuzzy sets, and major applications of fuzzy computing.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"6 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133111352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
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