Machine Learning
Mostrando 37-48 de 313 artigos, teses e dissertações.
-
37. Using UAV for automatic lithological classification of open pit mining front
Abstract Mine planning is dependent on the natural lithologic features and on the definition of their limits. The geological model is constantly updated during the life of the mine, based on all the information collected so far, plus the knowledge developed from the exploration stage up to the mine closure. As the mine progresses, the amount of available dat
REM, Int. Eng. J.. Publicado em: 2019-03
-
38. USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
RESUMO Objetivo: refletir sobre o uso de ferramentas computacionais no método de mapeamento cruzado entre terminologias clínicas. Método: estudo de reflexão. Resultados: o método de mapeamento cruzado consiste na obtenção de listagem de termos, por meio de extração e normalização; ligação entre os termos da listagem e os da base de referên
Texto contexto - enferm.. Publicado em: 14/02/2019
-
39. The Future Digital Work Force: Robotic Process Automation (RPA)
Abstract The Robotic Process Automation (RPA) is a new wave of the future technologies. Robotic Process Automation is one of the most advanced technologies in the area of computers science, electronic and communications, mechanical engineering and information technology. It is a combination of both hardware and software, networking and automation for doing t
JISTEM J.Inf.Syst. Technol. Manag.. Publicado em: 10/01/2019
-
40. Multivariate Analysis and Machine Learning in Properties of Ultisols (Argissolos) of Brazilian Amazon
ABSTRACT: Ultisols are the most common soil order in the Brazilian Amazon. The Legal Amazon (LA) has an area of 5 × 106 km2, with few accessible areas, which restricts studies of soils at a detailed level. The pedological properties can be estimated more efficiently using statistical procedures and machine learning techniques, tools which are capable of rec
Rev. Bras. Ciênc. Solo. Publicado em: 06/12/2018
-
41. Digital Soil Mapping Using Machine Learning Algorithms in a Tropical Mountainous Area
ABSTRACT: Increasingly, applications of machine learning techniques for digital soil mapping (DSM) are being used for different soil mapping purposes. Considering the variety of models available, it is important to know their performance in relation to soil data and environmental variables involved in soil mapping. This paper investigated the performance of
Rev. Bras. Ciênc. Solo. Publicado em: 14/11/2018
-
42. O futuro está chegando: perspectivas promissoras sobre o uso de machine learning no transplante renal
Resumo Introdução: A predição de resultados pós-transplante é clinicamente importante e envolve vários problemas. Os atuais modelos de previsão baseados em padrões estatísticos são muito complexos, difíceis de validar e não fornecem previsões precisas. Machine Learning, é uma técnica estatística que permite que o computador faça previsões
J. Bras. Nefrol.. Publicado em: 18/10/2018
-
43. Modeling of stem form and volume through machine learning
Abstract Taper functions and volume equations are essential for estimation of the individual volume, which have consolidated theory. On the other hand, mathematical innovation is dynamic, and may improve the forestry modeling. The objective was analyzing the accuracy of machine learning (ML) techniques in relation to a volumetric model and a taper function f
An. Acad. Bras. Ciênc.. Publicado em: 18/10/2018
-
44. Prediction of soil CO2 flux in sugarcane management systems using the Random Forest approach
ABSTRACT: The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two differ
Sci. agric. (Piracicaba, Braz.). Publicado em: 2018-08
-
45. Vegetation Image as Bayesian Predictor for Radio Propagation in Complex Environments Using Unscented Transform
Abstract Vegetation is considered a complex environment for analysis of scattering and attenuation in radio propagation phenomena. Satellite image processing can improve planning of radio systems with a vegetation attenuation predictor. In this research, the prediction is based on the correlation of more than 56% between RGB pixel values and vegetation atten
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2018-06
-
46. Assessing the risk zones of Chagas' disease in Chile, in a world marked by global climatic change
BACKGROUND Vector transmission of Trypanosoma cruzi appears to be interrupted in Chile; however, data show increasing incidence of Chagas' disease, raising concerns that there may be a reemerging problem. OBJECTIVE To estimate the actual risk in a changing world it is necessary to consider the historical vector distribution and correlate this distribution
Mem. Inst. Oswaldo Cruz. Publicado em: 2018-01
-
47. INFORMATION TOKEN DRIVEN MACHINE LEARNING FOR ELECTRONIC MARKETS: PERFORMANCE EFFECTS IN BEHAVIORAL FINANCIAL BIG DATA ANALYTICS
ABSTRACT Conjunct with the universal acceleration in information growth, financial services have been immersed in an evolution of information dynamics. It is not just the dramatic increase in volumes of data, but the speed, the complexity and the unpredictability of ‘big-data’ phenomena that have compounded the challenges faced by researchers and practit
JISTEM J.Inf.Syst. Technol. Manag.. Publicado em: 2017-12
-
48. Development of a skateboarding trick classifier using accelerometry and machine learning
Abstract Introduction Skateboarding is one of the most popular cultures in Brazil, with more than 8.5 million skateboarders. Nowadays, the discipline of street skating has gained recognition among other more classical sports and awaits its debut at the Tokyo 2020 Summer Olympic Games. This study aimed to explore the state-of-the-art for inertial measurement
Res. Biomed. Eng.. Publicado em: 2017-10