The use of Fuzzy Neural Structures to Increase the Reliability of Drilling Platforms

The total energy consumption in world is exponentially increasing. Infrastructural investment in wind energy project is the best solution for resolving energy problem. Selecting the site for wind farm is a complex process involving not only technical requirement, but also physical, economical, social, environmental and political requirements that may result in conflicting objectives, and that's why, it is necessary to create model that provides most desirable location for investing.The present paper uses fuzzy logic methodology and MATLAB to assess wind sites and decide which sites should be given the highest priority with respect to their benefits and costs. The criterion of evaluation using fuzzy logic is based on different parameters, i.e., wind resources, prevailing wind direction, above ground level, site capacity, soil conditions, site elevation, land cost, land roughness, temperature, cultural and environmental concerns, aviation/telecommunications conflicts, nearby resident's concerns, site environmental issue and distance to transmission line.For verification of our solutions, we had deployed the available data on the wind farm in Podveležje and based on our model, we may conclude that the site selection is quite good.

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“…Fuzzy logic has a wide range of utilizations in decision making since it condenses a large amount of parameters into smaller fuzzy sets [11].…”

Section: Fuzzy Logic Methodology For Decision Makingmentioning

confidence: 99%

Model of Fuzzy Logic for Selection Infrastructural Investment Project of Wind Farm Locations

Aljicevic¹,

Kostić²,

Dautbašić³

et al. 2016

Proceedings of the 27th International DAAAM Symposium 2016

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“…possible to explain the maximum value of observed in pilot researches [5,7] On the assumption of engineering aspects of of horizontal type for process optimization of epitaxy operations and movement of a flow of the Investigational studies confirmed that separation points and flow reattachment, separating emergence of a difficult heating pattern on a substrate surface even in case of the heating system. This influence is defined b susceptor, the inflow speed of gas of outflow of gas, the character of a current of gas drainage and a level of its heating reactor [8][9].…”

Section: Influence Of Location Of Stagnation Point Of Flow and Changementioning

confidence: 99%

Optimization Problem of Thermal Field on Surface of Revolving Susceptor in Vapor-Phase Epitaxy Reactor

Zhilenkov

Chernyi

Nyrkov

et al. 2017

IOP Conf. Ser.: Earth Environ. Sci.

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The use of such semiconductors allows obtaining full-color RGB light sources, increasing record density of a digital data storage device, getting high-capacity and efficient sources of white light. Electronic properties of such semi-conductors allow using them as a basis for high-power and high-frequency transistors and other electronic devices, the specifications of which are competitive with those of SiC-based devices. Only since 2000, the technology of cultivation of crystals III-N of group has come to the level of wide recognition by both abstract science, and the industry that has led to the creation of the multi-billion dollar market. And this is despite a rather low level of development of the production technology of devices on the basis of III-N of materials. The progress that has happened in the last decade requires the solution of the main problem, constraining further development of this technology today -ensuring cultivation of III-N structures of necessary quality. For this purpose, it is necessary to solve problems of the analysis and optimization of processes in installations of epitaxial growth, and, as a result, optimization of its constructions.

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“…The ANFIS structure is based on an artificial neural network and consists of five layers in which the neurons have different structures and perform different functions [19]. The proposed structure is designed to respond to the analyzed problem.…”

Section: Anfismentioning

confidence: 99%

Gait Phase Recognition for Exoskeleton Control Using Adaptive Neuro Fuzzy Inference System

Broniszewski¹,

Dabros²,

Iwaniec³

et al. 2017

DAAAM Proceedings

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Pressure measurement at the foot-ground contact zone provides necessary information for detecting the phases of the human gait. The human gait is a complicated process and, therefore, it is not possible to distinguish its stages simply by comparing the foot-ground surface pressure to threshold values. In this paper we propose a new method for human gait phases recognition using an adaptive network-based fuzzy inference system which processes data measured by pressure sensors located underneath footbed inserts. This method is intended to bring some additional information to the lower limb exoskeleton control system as well as for gait diagnostic purposes. The device uses only three pressure sensors for each foot. In order to verify the results of the study, measurements with sensors placed under the footbed inserts has been performed and the pressure at the foot-ground contact points during the walk has been investigated. Twelve models of gait phase classifiers were created. The performance of each classifier has been tested for a previously unknown pressure pattern that corresponds to the natural gait. Based on the quality of gait matching the test run, the best model of the classifier was selected.

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The use of Fuzzy Neural Structures to Increase the Reliability of Drilling Platforms

Cited by 21 publications

References 4 publications

Model of Fuzzy Logic for Selection Infrastructural Investment Project of Wind Farm Locations

Model of Fuzzy Logic for Selection Infrastructural Investment Project of Wind Farm Locations

Optimization Problem of Thermal Field on Surface of Revolving Susceptor in Vapor-Phase Epitaxy Reactor

Gait Phase Recognition for Exoskeleton Control Using Adaptive Neuro Fuzzy Inference System

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