Navegando por Assunto "Random forest"

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Acesso aberto (Open Access)
Algoritmos para seleção de metodologias de avaliação de softwares educacionais
(Universidade Federal do Pará, 2023-09-26) CASTILHO, Janize Monteiro de; FARIAS, Fabricio de Souza; http://lattes.cnpq.br/1521079293982268; https://orcid.org/0000-0003-4344-6953
In order to assist the teaching-learning processes, many teachers have decided to use Educational Software (ES) in their classrooms. However, to choose a ES as a teaching resource it is essential to endorse the methodology used by the teacher, once it needs to be pedagogically and functionally appropriate to meet the needs and objectives present in the classroom. Also, it is necessary to use mechanisms that the ES endorses to verify its adequacy to the professor’s objectives. Currently, it is verified that there are various techniques and methodologies available in the literature for ES assessment, but there is still no solution for decision making and selection of a ES that fully addresses the profiles of users and their different needs to be met by certain methodological application, or that arises from demand originating from the development of solutions based on demand and with a low capacity for generalization in terms of practical application. In this way, solutions are available without standardization and that several times do not take into consideration criteria relating to quality, measurement scales and verification procedures of the ES. This heterogeneity makes the evaluation of an ES very difficult, since the subjectivity in the selection of ES evaluation methodology can produce inconclusive results. Given this context, this work created a quality model that considers 24 ES assessment methodologies available in the literature and aims to automate the selection of ES assessment methodology based on the application of artificial intelligence (AI) algorithms, reducing the possibility of subjectivity in the screening process. During the investigation we used Natural Language Processing (NLP), Random Forest, k-Nearest Neighbors and Artificiais Neurais Networks. In all research scenarios, the natural language algorithm was combined with other algorithms, offering a solution based on the application of hybrid and loosely coupled AI algorithms, with excellent results. In this way, simulations were carried out considering NLP+Random Forest, NLP+k-Nearest Neighbors and NLP+Artificial Neurais Networks. After the simulations, the results indicate that it is possible to determine the best ES assessment methodology using AI algorithms, with the best results obtained with the combination of NLP+Random Forest.
Acesso aberto (Open Access)
ClasSIS: uma metodologia para classificação supervisionada de imagens de satélite em áreas de assentamento localizados na Amazônia
(Universidade Federal do Pará, 2015-03-12) MONTEIRO, Flavia Pessoa; FRANCÊS, Carlos Renato Lisboa; http://lattes.cnpq.br/7458287841862567
Amazon has one of the most complex and diversified biome of the planet. Its environmental preservation has an impact in the global scenario. However, besides the environmental factors, the complexity of the region involves other different aspects such as social, economical and cultural. In fact, they are intrinsically interrelated in such a way, that, for example, cultural features may affect land use/land cover. Moreover, depending on the scale of such changes, there may be consequences on the planet. Due to the criticality involving the region, several actions of governments, organizations and social movements and the international community, has been trying to rationalize the land use/land cover, in order to create a sustainable exploitation of available natural resources. An important government program is based on the creation of settlements, with respective support, with regard to certain infrastructure financing, machinery, seeds and seedlings, technical assistance, etc. However, despite the efforts made, the solution is extremely complex, given the extensive correlation of factors to be assessed and combined in search of success and improvement of such programs. So, because of all complexity involved, it is of paramount importance that there are methodologies that contemplate the complexity and inherent interdisciplinarity. Intending to have a closer look at this whole issue, an Amazonian set of institutions drew up and approved the project Skills Development and Training of Human Resources for Degraded Areas Recovery in Settlement Projects in Amazonian Areas – Public Notice Nº047 / 2012 - CAPES/Pró-Amazônia Programme. This work presents an innovative methodology for land use/land cover analysis, in projects of settlements located in the Amazon, as part of the above mentioned. Such methodology comprises two modules (image processing, and classification and patterns extraction), each module is subdivided into steps to performing their primary functions. The methodology proposed in this work, which has a high degree of generalization, aims to categorize the land use/land cover, through the association of each pixel to a predefined thematic class. In order to validate the proposed strategy, case studies are carried out in settlements located at the Southeast region of the Stat eof Pará, in the Brazilian Amazon.