Papers by Keyword: Membership Function

Abstract: The constant evolution of the energy industry, has introduced the need for ongoing research studies about climate change due to its direct action on the production of alternative energies. Thus, they have focused on developing predictive algorithms in order to resolve, in an early way, the climate action on each point of energy production. In the development of this work, the ANFIS algorithm and information from the NASA Langley research center virtual database were implemented. They being oriented to the analysis and prediction of solar radiation over the geographic area of the Nueva Granada Military University campus, Cajicá, Colombia, with the purpose of making appropriate use of the power generating system located in the zone. The development of such systems, would allow the early identification of solar radiation that can be present in different geographical areas of Colombia, in order to provide the necessary power to cover the electricity demand required in each region, achieving as results an approximation error less than 1%.

Abstract: The authors suggest the models of competitiveness assessment of engineering products at the early stages of the product life cycle. The criteria-based approach and the machinery of fuzzy sets theory are applied when developing the models. The model of consumers’ preferences forecasting allows calculating the prospective demand, motivation of consumer behavior, their attitude to the supplied product. The model based on the pair-wise comparison approach calculates fuzzy sets of various degrees of product competitiveness. The model of engineering product rating ensures rational selection of alternatives under the conditions of collective selection at all stages of the product life cycle.

Abstract: In order to improve the pump station control quality a special case of fuzzy controllers has been suggested to use, in which both the input and output variables are represented by a set of mutually non-overlapping terms of the rectangular shape of the membership function (precise terms). As it has been found out there is only one term in this set at any moment of time that is equal to a logical unit, whereas in the production rules system operating such terms, at any arbitrary moment of time, only one production rule antecedent is equal to a logical unit. This allows without losing of the control adequacy in each controller production system scanning cycle not to execute it completely, but solely as far as the rule, whose antecedent at a given moment is equal the logical unit, which also offers immense opportunities to increase the controller speed. In fuzzy controllers with precise terms, unlike the conventional fuzzy controllers the control precision has been shown to be invariant with respect to the complexity of the production rules conditional part structure. It is now clear that precision of fuzzy controllers with precise terms in the control systems as represented by verbal models is compatible with PID-controllers precision while using them to control the linear process facilities.

Abstract: As pumps and pumping stations of oil collecting, maintaining reservoir pressure, transportation and treatment processes account for over 50 % of oil and gas enterprises estimated total cost of electricity, relevant issue is the development and application of intelligent control systems for energy efficiency of these processes. For the booster pump station as a multivariable nonlinear control object are proposed: a structure in which the function of regulating valves transferred to the pumps with frequency speed control; conceptual model with seven inputs and five outputs (adjustable) variables, which is the basis for constructing three-dimensional fuzzy controller with not-fuzzy terms to stabilize and improve the energy efficiency of oil transportation and treatment processes and minimize energy losses. In this paper we propose a control system of pumping station on the basis of multidimensional fuzzy logic controller with compensation of the mutual influence of control loops in the form of an additional system of production rules that helped to stabilize the liquid level at 2.5 m given level with an absolute error of ± 0.2 m and thus improve quality oil emulsion on the installation of oil and gas refining central collection point.

Abstract: This paper studied the application of fuzzy comprehensive evaluation in meteorological mutation identification of load forecasting. It measured out a specific algorithm in meteorological mutation identification of ultra-short-term load forecasting, so that to improve the load forecasting accuracy and reduce the relative error. When using the fuzzy comprehensive evaluation method, set the membership function and factor right based on the characteristics of a province for the summer weather factors, and measure the mutation membership value with the appropriate operator, which can provide a reference for the study of meteorology identification. The result shows that using fuzzy comprehensive evaluation to identify meteorological mutation has good usability and accuracy.

Abstract: Reducing environmental pollution and achieving economic operation have become focus of the research about micro-grid (MG). The minimum operating cost and the minimum pollution emission cost are taken as optimizing objects, and the multi-object optimizing model of MG is established. The membership function is used to process multi-objective function, then the conversion of multi-object to single object is achieved. Genetic Algorithm is used to optimize the operating state of each unit, then the best operation mode is formed.

Abstract: This paper presents three models as a potential decision making method for selecting the best baseball, field hockey, and women’s basketball NCAA Division I coaches. Five indicators, synthesized coaching efficiency, winning percentage, consecutive championship, achievement index and gender, are introduced to give a comprehensive evaluation of coaching ability. The preliminary served as a filter model to screen out less capable coaches and a robust ranking within top 10 is achieved. The Data Envelopment Analysis (DEA) model takes the time line horizon into consideration, and helps find less efficient coaches. By comparing the first two models, we obtain a reasonable assessment of coaches from different time period. Finally, by applying the Analytical Hierarchy Process (AHP), minor changes in judgment matrices can be made to adjust the ratio of male to female in the top 5 coaches.

Abstract: The authors suggest the models for assessing the competitiveness of innovative engineering products (IEP): a model for forecasting the consumer’s preferences for IEP; a model for calculating fuzzy sets of alternatives of various competitiveness degrees at the early stages of research; integrated model for IEP competitiveness assessment with consideration to the stages of production, marketing and operation, the model for the rating assessment of alternatives. The paper considers the model for forming an expert committee involving fuzzy inference. The interrelation of models is shown with consideration to the life cycle of innovations.

Abstract: Computer teaching should emphasize the engineering practicality, creativity, and pay more attention to the project and its application. It is important to evaluate the teaching effect. An evaluation system and corresponding algorithm are presented in this paper. There is a certain correlation between some evaluation factors, and the factors can be divided into key factors and secondary factors by rough set. The evaluation algorithm based on the key factors can reduce redundant factors and improve the efficiency. We designed a clustering algorithm based on fuzzy set on evaluation entities, which can reduce the dada size and improve the accuracy of the algorithm. Through the example analysis the algorithm of factors reduction based on rough set and clustering method based on fuzzy set are described in detail.

Abstract: Web text exists non-certain and non-structure contents ,and it is difficult to cluster the text by normal classification methods. We propose a web text clustering algorithm based on fuzzy set to increase the computing accuracy with the web text. After abstracting the key words of the text, we can look it as attributes and design the fuzzy algorithm to decide the membership of the words. The algorithm can improve the algorithm complexity of time and space, increase the robustness comparing to the normal algorithm. To test the accuracy and efficiency of the algorithm, we take the comparative experiment between pattern clustering and our algorithm. The experiment shows that our method has a better result.