دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — بخش نهم
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 | Manufacturing intelligence and innovation for digital manufacturing and operational excellence |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Chen-Fu Chien, Mitsuo Gen, Yongjiang Shi, Chia-Yu Hsu |
| چکیده / توضیح | Global manufacturing networks and supply chains are facing ongoing dynamic changes in the evolutionary business ecosystems. The introduction of new process technologies and the advances in manufacturing intelligence capabilities are having profound effects on the strategies, decisions, management, and operations involved in manufacturing (Chien et al. 2007; Leachman et al. 2007). While big data is accumulated due to the fully automation manufacturing facilities and logistics systems for business integration, various solutions and techniques are developed to extract useful information and derive effective intelligence to address new challenges such as cycle time reduction (Kuo et al. 2011; Chien et al. 2011), defect diagnosis (Hsu and Chien 2007; Liu and Chien 2013), demand forecast (Chien et al. 2010), equipment management (Chien et al. 2008; Hsu et al. 2012; Chien et al. 2013a), human capital (Chen and Chien 2011), and bio informatics (Lin and Chien 2009). In particular, manufacturing ... |
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| عنوان اصلی مقاله | A metaheuristic for fast machining error compensation |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Roman Stryczek |
| چکیده / توضیح | In case of complex parts machining or multi-directional machining in multi-part fixtures the error compensation in multi-dimensional decision space poses a difficult problem. The article focuses on the limitation of defective products by means of systematic increase of the remaining error budget due to correction of the setup data. A vectorial equation for machine tool space description is presented. The development of geometric dimensioning and tolerancing scheme to the levels connected with the setup data is proposed. The optimization algorithm used here is based on the paradigm particle swarm optimization (PSO), but it includes a few significant modifications inspired by the growth of the coral reef thus the name of the method—coral reefs inspired particle swarm optimization (CRIPSO). CRIPSO has been compared with three other popular metaheuristics: classic PSO, genetic algorithm, and cuckoo optimization algorithm. There is a practical example in this article. |
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| عنوان اصلی مقاله | Hypermobile Robots – the Survey |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Grzegorz Granosik |
| چکیده / توضیح | This article presents a survey on hypermobile robots – a group of articulated mobile robots that typically comprise of several segments with powered wheels, tracks, or legs to propel the vehicle forward. Segments are connected by 2- or 3-degree-of-freedom (DOF) joints that may or may not be powered and provide better mobility as compared with regular mobile robots. The origins are analyzed and over 14 projects are compared in order to find the best methodology of designing and developing hypermobile robots. |
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| عنوان اصلی مقاله | Determination of bone porosity based on histograms of 3D μCT images |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | M. Cieszko, Z. Szczepański, P. Gadzała |
| چکیده / توضیح | A new method is proposed for direct determination of bone porosity based on histograms of 3D µCT scans and for precise definition of the global image segmentation threshold, preserving assessed porosity in the reconstructed binary image of the bone sample. In this method, the normed histogram is considered to be a probability distribution of voxel density (CT number or gray level) in the scan. It is a linear combination of two distributions characterizing the frequency of occurrence of voxels of pore and matrix type with various densities. Volume porosity, in this model, defines the probability of pore voxel occurrence in the whole set of voxels in the scan of the sample. This parameter and the parameters of both probability distributions are determined by an optimization method. The new method was used to determine the porosity and segmentation thresholds for µCT images of two 3D samples of human cancellous bone. The results were compared with those determined by the standard method and Otsu’s method. The new method allows the porosity and the image segmentation threshold to be determined even in cases where use of the other methods is questionable or impossible. |
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| عنوان اصلی مقاله | Optimisation of NMR dynamic models I. Minimisation algorithms and their performance within the model-free and Brownian rotational diffusion spaces |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Edward J. d’Auvergne, Paul R. Gooley |
| چکیده / توضیح | The key to obtaining the model-free description of the dynamics of a macromolecule is the optimisation of the model-free and Brownian rotational diffusion parameters using the collected R 1, R 2 and steady-state NOE relaxation data. The problem of optimising the chi-squared value is often assumed to be trivial, however, the long chain of dependencies required for its calculation complicates the model-free chi-squared space. Convolutions are induced by the Lorentzian form of the spectral density functions, the linear recombinations of certain spectral density values to obtain the relaxation rates, the calculation of the NOE using the ratio of two of these rates, and finally the quadratic form of the chi-squared equation itself. Two major topological features of the model-free space complicate optimisation. The first is a long, shallow valley which commences at infinite correlation times and gradually approaches the minimum. The most severe convolution occurs for motions on two timescales in which the minimum is often located at the end of a long, deep, curved tunnel or multidimensional valley through the space. A large number of optimisation algorithms will be investigated and their performance compared to determine which techniques are suitable for use in model-free analysis. Local optimisation algorithms will be shown to be sufficient for minimisation not only within the model-free space but also for the minimisation of the Brownian rotational diffusion tensor. In addition the performance of the programs Modelfree and Dasha are investigated. A number of model-free optimisation failures were identified: the inability to slide along the limits, the singular matrix failure of the Levenberg–Marquardt minimisation algorithm, the low precision of both programs, and a bug in Modelfree. Significantly, the singular matrix failure of the Levenberg–Marquardt algorithm occurs when internal correlation times are undefined and is greatly amplified in model-free analysis by both the grid search and constraint algorithms. The program relax (http://www.nmr-relax.com) is also presented as a new software package designed for the analysis of macromolecular dynamics through the use of NMR relaxation data and which alleviates all of the problems inherent within model-free analysis. |
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| عنوان اصلی مقاله | Bridging logic and kernel machines |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Michelangelo Diligenti, Marco Gori, Marco Maggini, Leonardo Rigutini |
| چکیده / توضیح | We propose a general framework to incorporate first-order logic (FOL) clauses, that are thought of as an abstract and partial representation of the environment, into kernel machines that learn within a semi-supervised scheme. We rely on a multi-task learning scheme where each task is associated with a unary predicate defined on the feature space, while higher level abstract representations consist of FOL clauses made of those predicates. We re-use the kernel machine mathematical apparatus to solve the problem as primal optimization of a function composed of the loss on the supervised examples, the regularization term, and a penalty term deriving from forcing real-valued constraints deriving from the predicates. Unlike for classic kernel machines, however, depending on the logic clauses, the overall function to be optimized is not convex anymore. An important contribution is to show that while tackling the optimization by classic numerical schemes is likely to be hopeless, a stage-based learning scheme, in which we start learning the supervised examples until convergence is reached, and then continue by forcing the logic clauses is a viable direction to attack the problem. Some promising experimental results are given on artificial learning tasks and on the automatic tagging of bibtex entries to emphasize the comparison with plain kernel machines. |
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| عنوان اصلی مقاله | ILP turns 20 |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Stephen Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter Flach, Katsumi Inoue, Ashwin Srinivasan |
| چکیده / توضیح | Inductive Logic Programming (ILP) is an area of Machine Learning which has now reached its twentieth year. Using the analogy of a human biography this paper recalls the development of the subject from its infancy through childhood and teenage years. We show how in each phase ILP has been characterised by an attempt to extend theory and implementations in tandem with the development of novel and challenging real-world applications. Lastly, by projection we suggest directions for research which will help the subject coming of age. |
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| عنوان اصلی مقاله | Using random forests to diagnose aviation turbulence |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | John K. Williams |
| چکیده / توضیح | Atmospheric turbulence poses a significant hazard to aviation, with severe encounters costing airlines millions of dollars per year in compensation, aircraft damage, and delays due to required post-event inspections and repairs. Moreover, attempts to avoid turbulent airspace cause flight delays and en route deviations that increase air traffic controller workload, disrupt schedules of air crews and passengers and use extra fuel. For these reasons, the Federal Aviation Administration and the National Aeronautics and Space Administration have funded the development of automated turbulence detection, diagnosis and forecasting products. This paper describes a methodology for fusing data from diverse sources and producing a real-time diagnosis of turbulence associated with thunderstorms, a significant cause of weather delays and turbulence encounters that is not well-addressed by current turbulence forecasts. The data fusion algorithm is trained using a retrospective dataset that includes objective turbulence reports from commercial aircraft and collocated predictor data. It is evaluated on an independent test set using several performance metrics including receiver operating characteristic curves, which are used for FAA turbulence product evaluations prior to their deployment. A prototype implementation fuses data from Doppler radar, geostationary satellites, a lightning detection network and a numerical weather prediction model to produce deterministic and probabilistic turbulence assessments suitable for use by air traffic managers, dispatchers and pilots. The algorithm is scheduled to be operationally implemented at the National Weather Service’s Aviation Weather Center in 2014. |
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| عنوان اصلی مقاله | Computational Meta-Ethics |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Gert-Jan C. Lokhorst |
| چکیده / توضیح | It has been argued that ethically correct robots should be able to reason about right and wrong. In order to do so, they must have a set of do’s and don’ts at their disposal. However, such a list may be inconsistent, incomplete or otherwise unsatisfactory, depending on the reasoning principles that one employs. For this reason, it might be desirable if robots were to some extent able to reason about their own reasoning—in other words, if they had some meta-ethical capacities. In this paper, we sketch how one might go about designing robots that have such capacities. We show that the field of computational meta-ethics can profit from the same tools as have been used in computational metaphysics. |
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| عنوان اصلی مقاله | Mobility and Network Management in Heterogeneous Networks |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Kostas Pentikousis, Ramon Agüero, Symeon Papavassiliou |
| چکیده / توضیح | Multiaccess and resource management, mobility management, and network management have emerged as core topics in the design, deployment and operation of current and future networks. The research activity in these areas has grown tremendously over the past decade, addressing the pressing need for ubiquitous and cost-efficient mobile broadband. At the same time, new possibilities and communications paradigms have emerged, bringing about the appearance of new challenges, which had not been considered so far. This special issue comprises peer-reviewed articles that provide answers to problems ranging from optimum access selection in overlapping mobile and wireless networks to mobile network virtualization to self-managed network architectures with QoS guarantees. |
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