دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — بخش دهم

منطق فازی (Fuzzy Logic) اولین بار در پی تنظیم نظریه مجموعه‌های فازی به وسیله پروفسور لطفی زاده (۱۹۶۵ میلادی) در صحنه محاسبات نو ظاهر شد. در واقع منطق فازی از منطق ارزش‌های «صفر و یک» نرم‌افزارهای کلاسیک فراتر رفته و درگاهی جدید برای دنیای علوم نرم‌افزاری و رایانه‌ها می‌گشاید، زیرا فضای شناور و نامحدود بین اعداد صفر و یک را نیز در منطق و استدلال‌های خود به کار می‌گیرد. در ادامه مقالات علمی انتشارات بین المللی اشپرینگر (Springer) در زمینه منطق فازی (Fuzzy Logic) برای دانلود آمده است. می توانید برای دانلود هر یک از مقالات از سرور دانلود متلب سایت، بر روی لینک دانلود هر یک از آن ها، کلیک کنید.

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دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — فهرست اصلی

عنوان اصلی مقاله MONET Special Half-Issue “Recent Advances on Communications and Networking in China”
نوع مقاله مقاله ژورنال
نویسندگان Victor C. M. Leung, Fumiyuki Adachi, Weixiao Meng, Qilian Liang
چکیده / توضیح Editorial:
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عنوان اصلی مقاله Fuzzy based Impulse Noise Reduction Method
نوع مقاله مقاله ژورنال
نویسندگان Ayyaz Hussain, Sohail Masood Bhatti, M. Arfan Jaffar
چکیده / توضیح In this paper, we propose an image filtering technique based on fuzzy logic control to remove impulse noise for low as well as highly corrupted images. The proposed method is based on noise detection, noise removal and edge preservation modules. The main advantage of the proposed technique over the other filtering techniques is its superior noise removal as well as detail preserving capability. Based on the criteria of peak-signal-to-noise-ratio (PSNR), mean square error (MSE), structural similarity index measure (SSIM) and subjective evaluation measure we have found experimentally that the proposed method provides much better performance than the state-of-the-art filters. To analyze the detail preservation capability of the proposed filter sensitivity analysis is performed by changing the detail preservation module to see its effects on the details (texture and edge information) of resultant image. This sensitivity analysis proves experimentally that significant image details have been preserved by the proposed method.
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عنوان اصلی مقاله A multi-objective hybrid genetic algorithm to minimize the total cost and delivery tardiness in a reverse logistics
نوع مقاله مقاله ژورنال
نویسندگان Jeong-Eun Lee, Kyung-Yong Chung, Kang-Dae Lee, Mitsuo Gen
چکیده / توضیح In the recent environmental protection the reverse logistics of the used product is one of the most important research topics. The reverse logistics is the process flow of used-products that are collected to be reproduced so that they can be sold again to customers after some processing. We propose a multi-objective hybrid genetic algorithm (mo-hGA) combined with Fuzzy Logic Controller (FLC) for efficiently dealing with multi-objective reverse logistics network (mo-RLN) problem. The aim of this paper is firstly to formulate mo-RLN model, and secondly to optimize it by mo-hGA method proposed with reusable system configuration. In particular two objective functions to be minimized total costs of mo-RLN, (i.e. fixed opening cost, transportation cost and inventory cost) and also minimized delivery tardiness in all periods are considered in the model. We will clear each objective function (i.e. total costs and total delivery tardiness), computational time and number of Pareto solutions with LINGO, pri-awGA (priority-based GA with adaptive weight approach) and mo-hGA proposed with numerical examples. For demonstrating the effectiveness of the proposed model, we evaluate with the numerical examples and simulate it with a bottles distilling/sale company as a case study in Busan, Korea.
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عنوان اصلی مقاله A generic framework for semantic video indexing based on visual concepts/contexts detection
نوع مقاله مقاله ژورنال
نویسندگان Nizar Elleuch, Anis Ben Ammar, Adel M. Alimi
چکیده / توضیح Providing a semantic access to video data requires the development of concept detectors. However, semantic concepts detection is a hard task due to the large intra-class and the small inter-class variability of content. Moreover, semantic concepts co-occur together in various contexts and their occurrence may vary from one to another. Thus, it is interesting to exploit this knowledge in order to achieve satisfactory performances. In this paper we present a generic semantic video indexing scheme, called SVI_REGIMVid. It is based on three levels of analysis. The first level (level1) focuses on low-level processing such as video shot boundary/key-frame detection, annotation tools, key-points detection and visual features extraction tools. The second level (level2) aims to build the semantic models for supervised learning of concepts/contexts. The third level (level3) enriches the semantic interpretation of concepts/contexts by exploiting fuzzy knowledge. The obtained experimental results are promising for a semantic concept/context detection process.
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عنوان اصلی مقاله Video analytics-based algorithm for monitoring egress from buildings
نوع مقاله مقاله ژورنال
نویسندگان Maciej Szczodrak, Andrzej Czyzewski
چکیده / توضیح A concept and a practical implementation of the algorithm for detecting of potentially dangerous situations related to crowding in passages is presented. An example of such a situation is a crush which may be caused by an obstructed pedestrian pathway. The surveillance video camera signal analysis performed in the online mode is employed in order to detect hold-ups near bottlenecks like doorways or staircases. The details of the implemented algorithm which uses the optical flow method combined with fuzzy logic are explained. The experiments were carried out on a set of gathered video recordings from the surveillance camera installed in the campus of Gdansk University of Technology. The results of experiments performed on gathered video recordings shows high efficiency of the algorithm.
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عنوان اصلی مقاله Rule-Based Learning Systems for Support Vector Machines
نوع مقاله مقاله ژورنال
نویسندگان Haydemar Núñez, Cecilio Angulo, Andreu Català
چکیده / توضیح In this article, we propose some methods for deriving symbolic interpretation of data in the form of rule based learning systems by using Support Vector Machines (SVM). First, Radial Basis Function Neural Networks (RBFNN) learning techniques are explored, as is usual in the literature, since the local nature of this paradigm makes it a suitable platform for performing rule extraction. By using support vectors from a learned SVM it is possible in our approach to use any standard Radial Basis Function (RBF) learning technique for the rule extraction, whilst avoiding the overlapping between classes problem. We will show that merging node centers and support vectors explanation rules can be obtained in the form of ellipsoids and hyper-rectangles. Next, in a dual form, following the framework developed for RBFNN, we construct an algorithm for SVM. Taking SVM as the main paradigm, geometry in the input space is defined from a combination of support vectors and prototype vectors obtained from any clustering algorithm. Finally, randomness associated with clustering algorithms or RBF learning is avoided by using only a learned SVM to define the geometry of the studied region. The results obtained from a certain number of experiments on benchmarks in different domains are also given, leading to a conclusion on the viability of our proposal.
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عنوان اصلی مقاله Asymmetric k -Means Clustering of the Asymmetric Self-Organizing Map
نوع مقاله مقاله ژورنال
نویسندگان Dominik Olszewski
چکیده / توضیح An asymmetric approach to clustering of the asymmetric self-organizing map is proposed. The clustering is performed using an improved asymmetric version of the well-known k -means algorithm. The improved asymmetric k -means algorithm is the second proposal of this paper. As a result, we obtain a two-stage fully asymmetric data analysis technique. In this way, we maintain the methodological consistency of the both utilized methods, because they are both formulated in asymmetric versions, and consequently, they both properly adjust to asymmetric relationships in analyzed data. The results of our experiments on real data confirm the effectiveness of the proposed approach.
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عنوان اصلی مقاله Fuzzy algorithm for estimating average breach widths of embankment dams
نوع مقاله مقاله ژورنال
نویسندگان Hasan G. Elmazoghi
چکیده / توضیح Dam breach width significantly influences peak breach outflow, inundation levels, and flood arrival time, but uncertainties inherent in the prediction of its value for embankment dams make its accurate estimation a challenging task in dam risk assessments. The key focus of this paper is to provide a fuzzy logic (FL) model for estimating the average breach width of embankment dams as an alternative to regression equations (RE). The FL approach is capable of handling nonlinear behavior, imprecision in discrete measurements, and parameter uncertainty. Historical data from 69 embankment dam failures are used in the development and testing of the FL model. Application of the FL model is also presented for estimating average breach widths of two case studies that have adequately documented data. The accuracy of the FL rule-based model is investigated using uncertainty analysis: the mean prediction error between the FL estimates and the observed average breach widths is very small (=0.03) and comparable to that achieved using the best available RE. Moreover, the FL uncertainty band is found to be approximately ±0.51 order of magnitude smaller than the ±0.56 order of magnitude achieved with the best available RE. The simulation results indicate the potential of the FL model to be used as a predictive tool for estimating the average breach width of embankment dams.
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عنوان اصلی مقاله Approximations by linear operators in spaces of fuzzy continuous functions
نوع مقاله مقاله ژورنال
نویسندگان Mark Burgin, Oktay Duman
چکیده / توضیح In this work, we further develop the Korovkin-type approximation theory by utilizing a fuzzy logic approach and principles of neoclassical analysis, which is a new branch of fuzzy mathematics and extends possibilities provided by the classical analysis. In the conventional setting, the Korovkin-type approximation theory is developed for continuous functions. Here we extend it to the space of fuzzy continuous functions, which contains a great diversity of functions that are not continuous. Furthermore, we give several applications, demonstrating that our new approximation results are stronger than the classical ones.
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عنوان اصلی مقاله Global in scope and regionally rich: an IndiSeas workshop helps shape the future of marine ecosystem indicators
نوع مقاله مقاله ژورنال
نویسندگان Yunne-Jai Shin, Alida Bundy, Lynne J. Shannon, Julia L. Blanchard, Ratana Chuenpagdee, Marta Coll, Ben Knight, Christopher Lynam, Gerjan Piet, Anthony J. Richardson, the IndiSeas Working Group
چکیده / توضیح This report summarizes the outcomes of an IndiSeas workshop aimed at using ecosystem indicators to evaluate the status of the world’s exploited marine ecosystems in support of an ecosystem approach to fisheries, and global policy drivers such as the 2020 targets of the Convention on Biological Diversity. Key issues covered relate to the selection and integration of multi-disciplinary indicators, including climate, biodiversity and human dimension indicators, and to the development of data- and model-based methods to test the performance of ecosystem indicators in providing support for fisheries management. To enhance the robustness of our cross-system comparison, unprecedented effort was put in gathering regional experts from developed and developing countries, working together on multi-institutional survey datasets, and using the most up-to-date ecosystem models.
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