3 resultados para Artificial intelligence -- Data processing
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
Artificial Intelligence techniques are applied to improve performance of a simulated oil distillation system. The chosen system was a debutanizer column. At this process, the feed, which comes to the column, is segmented by heating. The lightest components become steams, by forming the LPG (Liquefied Petroleum Gas). The others components, C5+, continue liquid. In the composition of the LPG, ideally, we have only propane and butanes, but, in practice, there are contaminants, for example, pentanes. The objective of this work is to control pentane amount in LPG, by means of intelligent set points (SP s) determination for PID controllers that are present in original instrumentation (regulatory control) of the column. A fuzzy system will be responsible for adjusting the SP's, driven by the comparison between the molar fraction of the pentane present in the output of the plant (LPG) and the desired amount. However, the molar fraction of pentane is difficult to measure on-line, due to constraints such as: long intervals of measurement, high reliability and low cost. Therefore, an inference system was used, based on a multilayer neural network, to infer the pentane molar fraction through secondary variables of the column. Finally, the results shown that the proposed control system were able to control the value of pentane molar fraction under different operational situations
Resumo:
Currently, several psychological and non-psychological tests can be found in publishes without standardization on procedures set in different psychological areas, like intelligence, emotional states, attitudes, social skills, vocation, preferences and others. The computerized psychological testing is a extension of traditional testing psychological practices. However, it has own psychometrics qualities, either by its matching in a computerized environment or by the extension that can be developed in it. The current research, developed from a necessity to study process of validity and reliability on a computerized test, drew a methodological structure to provide parallel applications in numerous kinds of operational groups, evaluating the influences of the time and approach in the computerization process. This validity refers to normative values groups, reproducibility in computerized applications process and data processing. Not every psychological test can be computerized. Therefore, our need to find a good test, with quality and plausible properties to transform in computerized application, leaded us to use The Millon Personality Inventory, created by Theodore Millon. This Inventory assesses personality according to 12 bipolarities distributed in 24 factors, distributed in categories motivational styles, cognitive targets and interpersonal relations. This instrument doesn t diagnose pathological features, but test normal and non adaptive aspects in human personality, comparing with Theodore Millon theory of personality. In oder to support this research in a Brazilian context in psychological testing, we discuss the theme, evaluating the advantages and disadvantages of such practices. Also we discuss the current forms in computerization of psychological testing and the main specific criteria in this psychometric specialized area of knowledge. The test was on-line, hosted in the site http://www.planetapsi.com, during the years of 2007 and 2008, which was available a questionnaire to describe social characteristics before test. A report was generated from the data entry of each user. An application of this test was conducted in a linear way through a national coverage in all Brazil regions, getting 1508 applications. Were organized nine groups, reaching 180 applications in test and retest subject, where three periods of time and three forms of retests for studies of on-line tests were separated. Parallel to this, we organized multi-application session offline group, 20 subjects who received tests by email. The subjects of this study were generally distributed by the five Brazilian regions, and were noticed about the test via the Internet. The performance application in traditional and on-line tested groups subsidies us to conclude that on-line application provides significantly consistency in all criteria for validity studied and justifies its use. The on-line test results were related not only among themselves but were similar to those data of tests done on pencil and paper (0,82). The retests results demonstrated correlation, between 0,92 and, 1 while multisessions had a good correlation in these comparisons. Moreover, were assessed the adequacy of operational criteria used, such as security, the performance of users, the environmental characteristics, the organization of the database, operational costs and limitations in this on-line inventory. In all these five items, there were excellent performances, concluding, also, that it s possible a self-applied psychometric test. The results of this work are a guide to question and establish of methodologies studies for computerization psychological testing software in the country
Resumo:
Educational Data Mining is an application domain in artificial intelligence area that has been extensively explored nowadays. Technological advances and in particular, the increasing use of virtual learning environments have allowed the generation of considerable amounts of data to be investigated. Among the activities to be treated in this context exists the prediction of school performance of the students, which can be accomplished through the use of machine learning techniques. Such techniques may be used for student’s classification in predefined labels. One of the strategies to apply these techniques consists in their combination to design multi-classifier systems, which efficiency can be proven by results achieved in other studies conducted in several areas, such as medicine, commerce and biometrics. The data used in the experiments were obtained from the interactions between students in one of the most used virtual learning environments called Moodle. In this context, this paper presents the results of several experiments that include the use of specific multi-classifier systems systems, called ensembles, aiming to reach better results in school performance prediction that is, searching for highest accuracy percentage in the student’s classification. Therefore, this paper presents a significant exploration of educational data and it shows analyzes of relevant results about these experiments.