Algorithms Combination
Mostrando 1-12 de 82 artigos, teses e dissertações.
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1. Rapid Recognizing the Producing Area of a Tobacco Leaf Using Near-Infrared Technology and a Multi-Layer Extreme Learning Machine Algorithm
A novel recognition method was put forward to identify the producing areas of the flue-cured tobacco leaves rapidly and non-destructively by using a near-infrared (NIR) spectrometer and a multi-layer-extreme learning machine (ML-ELM) algorithm. In contrast to traditional linear discriminant analysis (LDA) and extreme learning machine (ELM) algorithms, the ac
Journal of the Brazilian Chemical Society. Publicado em: 2022
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2. Decision tree-based classification as a support to diagnosis in the Alzheimer’s disease continuum using cerebrospinal fluid biomarkers: insights from automated analysis
Objective: Cerebrospinal fluid (CSF) biomarkers add accuracy to the diagnostic workup of cognitive impairment by illustrating Alzheimer’s disease (AD) pathology. However, there are no universally accepted cutoff values for the interpretation of AD biomarkers. The aim of this study is to determine the viability of a decision-tree method to analyse CSF bioma
Brazilian Journal of Psychiatry. Publicado em: 2022
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3. Comparison of the intubation success rate between the intubating catheter and videolaryngoscope in difficult airways: a prospective randomized trial
Abstract Background: Several devices and algorithms have already been examined and compared for difficult airway management. However, there is no existing study comparing the success of the Intubating Catheter (IC) and the Videolaryngoscope (VL) in patients who are difficult to intubate. We aimed to compare Frova IC and McGrath VL in terms of intubation suc
Brazilian Journal of Anesthesiology. Publicado em: 2022
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4. Precision non-implantable neuromodulation therapies: a perspective for the depressed brain
Current first-line treatments for major depressive disorder (MDD) include pharmacotherapy and cognitive-behavioral therapy. However, one-third of depressed patients do not achieve remission after multiple medication trials, and psychotherapy can be costly and time-consuming. Although non-implantable neuromodulation (NIN) techniques such as transcranial magne
Braz. J. Psychiatry. Publicado em: 2020-08
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5. Comparison and Combination of Techniques for Determining the Parameters of a Magnetic Hysteresis Model
Abstract The Jiles-Atherton scalar hysteresis model presents five parameters used to represent the material tested and used to calculate the magnetic losses. This article presents a comparative analysis of the performance of two methods of identifying these parameters. In the first method, the equations of Jiles-Atherton were assembled into a single non-line
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 12/09/2019
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6. 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
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7. 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
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8. Research and Applications of Shop Scheduling Based on Genetic Algorithms
ABSTRACT Shop Scheduling is an important factor affecting the efficiency of production, efficient scheduling method and a research and application for optimization technology play an important role for manufacturing enterprises to improve production efficiency, reduce production costs and many other aspects. Existing studies have shown that improved genetic
Braz. arch. biol. technol.. Publicado em: 20/10/2016
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9. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM
Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the networ
Braz. J. Chem. Eng.. Publicado em: 2016-03
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10. Developing and Multi-Objective Optimization of a Combined Energy Absorber Structure Using Polynomial Neural Networks and Evolutionary Algorithms
Abstract In this study a newly developed thin-walled structure with the combination of circular and square sections is investigated in term of crashworthiness. The results of the experimental tests are utilized to validate the Abaqus/ExplicitTM finite element simulations and analysis of the crush phenomenon. Three polynomial meta-models based on the evolved
Lat. Am. j. solids struct.. Publicado em: 2016
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11. Global microRNA profiles and signaling pathways in the development of cardiac hypertrophy
Hypertrophy is a major predictor of progressive heart disease and has an adverse prognosis. MicroRNAs (miRNAs) that accumulate during the course of cardiac hypertrophy may participate in the process. However, the nature of any interaction between a hypertrophy-specific signaling pathway and aberrant expression of miRNAs remains unclear. In this study, Spague
Braz J Med Biol Res. Publicado em: 11/04/2014
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12. On the status and role of instrumental images in contemporary science: some epistemological issues
The controversy over imageless thought versus picture thinking (especially via mechanical models), with the recent reconsideration of model-based reasoning in the physical sciences is briefly examined. The main focus of the article is on the role of instrumentally elicited images (scopic instruments, cameras, CCDs) in the sciences, especially in the physical
Sci. stud.. Publicado em: 2014