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

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 A comparison of Mamdani and Sugeno fuzzy based packet scheduler for MANET with a realistic wireless propagation model
نوع مقاله مقاله ژورنال
نویسندگان Oche Alexander Egaji, Alison Griffiths, Mohammad S. Hasan, Hong-Nian Yu
چکیده / توضیح The mobile nature of the nodes in a wireless mobile ad-hoc network (MANET) and the error prone link connectivity between nodes pose many challenges. These include frequent route changes, high packet loss, etc. Such problems increase the end-to-end delay and decrease the throughput. This paper proposes two adaptive priority packet scheduling algorithms for MANET based on Mamdani and Sugeno fuzzy inference system. The fuzzy systems consist of three input variables: data rate, signal-to-noise ratio (SNR) and queue size. The fuzzy decision system has been optimised to improve its efficiency. Both fuzzy systems were verified using the Matlab fuzzy toolbox and the performance of both algorithms were evaluated using the riverbed modeler (formally known as OPNET modeler). The results were compared to an existing fuzzy scheduler under various network loads, for constant-bit-rate (CBR) and variable-bit-rate (VBR) traffic. The measuring metrics which form the basis for performance evaluation are end-to-end delay, throughput and packet delivery ratio. The proposed Mamdani and Sugeno scheduler perform better than the existing scheduler for CBR traffic. The end-to-end delay for Mamdani and Sugeno scheduler was reduced by an average of 52% and 54%, respectively. The performance of the throughput and packet delivery ratio for CBR traffic are very similar to the existing scheduler because of the characteristic of the traffic. The network was also at full capacity. The proposed schedulers also showed a better performance for VBR traffic. The end-to-end delay was reduced by an average of 38% and 52%, respectively. Both the throughput and packet delivery ratio (PDR) increased by an average of 53% and 47%, respectively. The Mamdani scheduler is more computationally complex than the Sugeno scheduler, even though they both showed similar network performance. Thus, the Sugeno scheduler is more suitable for real-time applications.
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عنوان اصلی مقاله Model-based and fuzzy logic approaches to condition monitoring of operational wind turbines
نوع مقاله مقاله ژورنال
نویسندگان Philip Cross, Xiandong Ma
چکیده / توضیح It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to harsh operating conditions. These challenges mean there is a requirement for a high degree of maintenance. The data generated by monitoring systems can be used to obtain models of wind turbines operating under different conditions, and hence predict output signals based on known inputs. A model-based condition monitoring system can be implemented by comparing output data obtained from operational turbines with those predicted by the models, so as to detect changes that could be due to the presence of faults. This paper discusses several techniques for model-based condition monitoring systems: linear models, artificial neural networks, and state dependent parameter “pseudo” transfer functions. The models are identified using supervisory control and data acquisition (SCADA) data acquired from an operational wind firm. It is found that the multiple-input single-output state dependent parameter method outperforms both multivariate linear and artificial neural network-based approaches. Subsequently, state dependent parameter models are used to develop adaptive thresholds for critical output signals. In order to provide an early warning of a developing fault, it is necessary to interpret the amount by which the threshold is exceeded, together with the period of time over which this occurs. In this regard, a fuzzy logic-based inference system is proposed and demonstrated to be practically feasible.
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عنوان اصلی مقاله Modeling and Control of High-Velocity Oxygen-Fuel (HVOF) Thermal Spray: A Tutorial Review
نوع مقاله مقاله ژورنال
نویسندگان Mingheng Li, Panagiotis D. Christofides
چکیده / توضیح This work provides a tutorial overview of recent research efforts in modeling and control of the high-velocity oxygen-fuel (HVOF) thermal spray process. Initially, the modeling of the HVOF thermal spray, including combustion, gas dynamics, particle in-flight behavior, and coating microstructure evolution is reviewed. The influence of the process operating conditions as predicted by the fundamental models on particle characteristics and coating microstructure is then discussed and compared with experimental observations. Finally, the issues of measurement and automatic control are discussed and comments on potential future research efforts are made.
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عنوان اصلی مقاله Sensors in Spray Processes
نوع مقاله مقاله ژورنال
نویسندگان P. Fauchais, M. Vardelle
چکیده / توضیح This paper presents what is our actual knowledge about sensors, used in the harsh environment of spray booths, to improve the reproducibility and reliability of coatings sprayed with hot or cold gases. First are described, with their limitations and precisions, the different sensors following the in-flight hot particle parameters (trajectories, temperatures, velocities, sizes, and shapes). A few comments are also made about techniques, still under developments in laboratories, to improve our understanding of coating formation such as plasma jet temperature measurements in non-symmetrical conditions, hot gases heat flux, particles flattening and splats formation, particles evaporation. Then are described the illumination techniques by laser flash of either cold particles (those injected in hot gases, or in cold spray gun) or liquid injected into hot gases (suspensions or solutions). The possibilities they open to determine the flux and velocities of cold particles or visualize liquid penetration in the core of hot gases are discussed. Afterwards are presented sensors to follow, when spraying hot particles, substrate and coating temperature evolution, and the stress development within coatings during the spray process as well as the coating thickness. The different uses of these sensors are then described with successively: (i) Measurements limited to particle trajectories, velocities, temperatures, and sizes in different spray conditions: plasma (including transient conditions due to arc root fluctuations in d.c. plasma jets), HVOF, wire arc, cold spray. Afterwards are discussed how such sensor data can be used to achieve a better understanding of the different spray processes, compare experiments to calculations and improve the reproducibility and reliability of the spray conditions. (ii) Coatings monitoring through in-flight measurements coupled with those devoted to coatings formation. This is achieved by either maintaining at their set point both in-flight and certain spray parameters (spray pattern, coating temperature…), or defining a good working area through factorial design, or using artificial intelligence based on artificial neural network (ANN) to predict particle in-flight characteristics and coating structural attributes from the knowledge of processing parameters.
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عنوان اصلی مقاله An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube
نوع مقاله مقاله ژورنال
نویسندگان Samad Ahadian, Yoshiyuki Kawazoe
چکیده / توضیح Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS) is presented to solve this problem. The proposed ANFIS approach can construct an input–output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input–output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down.
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عنوان اصلی مقاله Dealing with the Uncertainty of Having Incomplete Sources of Geo-Information in Spatial Planning
نوع مقاله مقاله ژورنال
نویسندگان L. A. E. Vullings, C. A. Blok, C. G. A. M. Wessels, J. D. Bulens
چکیده / توضیح The Dutch spatial planning legal act of 2008 was aimed at improving efficiency and effectiveness in the development, evaluation and monitoring of spatial planning policy (Ministry of VROM, 2006a). One of the main effects of this legal act was the widespread availability and use of digital spatial plans (Ministry of VROM 2006a, b). This reform led to the expectation that all digital spatial plans would be exchangeable and comparable. In practice, this exchange and comparison required carrying out complex procedures due to uncertainty caused by differences in the scope of spatial plans as well as their intended use. Furthermore the uncertainty resulted in a lack of confidence in spatial plans by policymakers and supporting GIS staff. Our overarching research question was: how can uncertainty caused by incomplete geo-information sources be dealt with? We proposed two techniques—fuzzy logic and visualisation—for policy makers to deal with uncertainty resulting from incomplete geo-information sources in spatial planning at the regional and national planning levels. We used two case studies in the Netherlands to illustrate the results of applying these techniques. The fuzzy set theory provides extra information by converting the discrete borders of continuous objects into fuzzy borders that improve the resemblance to the real object and thus make it more realistic. As shown in the second case study, visualisation also improves the degree of realism and thus provides additional information. Both case studies showed that providing additional information reduces the uncertainty felt by policymakers.
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عنوان اصلی مقاله Space Physics Interactive Data Resource—SPIDR
نوع مقاله مقاله ژورنال
نویسندگان Mikhail Zhizhin, Eric Kihn, Rob Redmon, Dmitry Medvedev, Dmitry Mishin
چکیده / توضیح SPIDR (Space Physics Interactive Data Resource) is a standard data source for solar-terrestrial physics, functioning within the framework of the ICSU World Data Centers. It is a distributed database and application server network, built to select, visualize and model historical space weather data distributed across the Internet. SPIDR can work as a fully-functional web-application (portal) or as a grid of web-services, providing functions for other applications to access its data holdings.
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عنوان اصلی مقاله The Analysis of Vodka: A Review Paper
نوع مقاله مقاله ژورنال
نویسندگان Paulina Wiśniewska, Magdalena Śliwińska, Tomasz Dymerski, Waldemar Wardencki, Jacek Namieśnik
چکیده / توضیح Vodka is the most popular alcoholic beverage in Poland, Russia and other Eastern European countries, made from ethyl alcohol of agricultural origin that has been produced via fermentation of potatoes, grains or other agricultural products. Despite distillation and multiple filtering, it is not possible to produce 100 % ethanol. The solution with a minimum ethanol content of 96 %, which is used to produce vodkas, also contains trace amounts of other compounds such as, esters, aldehydes, higher alcohols, methanol, acetates, acetic acid and fusel oil. Regarding that fact, it is very important to carry on research on the analysis of the composition and verifying the authenticity of the produced vodkas. This paper summarizes the studies of vodka composition and verifying the authenticity and detection of falsified products. It also includes the methods for analysing vodkas, such as: using gas, ion and liquid chromatography coupled with different types of detectors, electronic nose, electronic tongue, conductivity measurements, isotope analysis, atomic absorption spectroscopy, near infrared spectroscopy, spectrofluorometry and mass spectrometry. In some cases, the use of chemometric methods and preparation techniques were also described.
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عنوان اصلی مقاله A review of closed-loop reservoir management
نوع مقاله مقاله ژورنال
نویسندگان Jian Hou, Kang Zhou, Xian-Song Zhang, Xiao-Dong Kang, Hai Xie
چکیده / توضیح The closed-loop reservoir management technique enables a dynamic and real-time optimal production schedule under the existing reservoir conditions to be achieved by adjusting the injection and production strategies. This is one of the most effective ways to exploit limited oil reserves more economically and efficiently. There are two steps in closed-loop reservoir management: automatic history matching and reservoir production optimization. Both of the steps are large-scale complicated optimization problems. This paper gives a general review of the two basic techniques in closed-loop reservoir management; summarizes the applications of gradient-based algorithms, gradient-free algorithms, and artificial intelligence algorithms; analyzes the characteristics and application conditions of these optimization methods; and finally discusses the emphases and directions of future research on both automatic history matching and reservoir production optimization.
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عنوان اصلی مقاله A neural network model approach to athlete selection
نوع مقاله مقاله ژورنال
نویسندگان Adam Maszczyk, Adam Zając, Igor Ryguła
چکیده / توضیح In order to determine the usefulness of neural models in optimisation of recruitment processes, statistical analyses were carried out on measured results of javelin throwers using a full take off. A group of 140 Polish junior javelin throwers took part in the research. In order to choose the optimum combination of model parameters the Hellwig method was used. Linear and multilayer perceptron neural models were constructed and used to calculate combinations of variables. Statistical analysis of the results showed that the linear model was not able to describe precisely the relationship between the dependent variable and independent variables for the investigated group of young javelin throwers. For the investigated group, the perceptron network with a 4-3-2-1 structure gave the best predictive relationship for sports results of the javelin throwers.
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