1. Application of artificial neural networks in the study of Mozzarella cheese salting

Abstract A highly efficient tool that has stood out in data processing and treatment is Artificial Neural Networks (ANNs). Self-organized maps (SOM), which is a type of ANNs, are easy-to-view computational models that simulate information processing and knowledge acquisition. Applying this tool, we analyzed the behavior of the film formed on the mozzarella c

Food Sci. Technol. Publicado em: 2021-06

2. ARTIFICIAL NEURAL NETWORK-BASED METHOD TO IDENTIFY FIVE VARIETIES OF EGYPTIAN FABA BEAN ACCORDING TO SEED MORPHOLOGICAL FEATURES

ABSTRACT One of the new crop varieties that have been adopted for high yield is the Egyptian faba bean. However, poor-quality faba bean has reduced economic value. Quality evaluation is thus important and can be performed using computational intelligence. We developed a robust method based on morphological features and artificial neural network for quality g

Eng. Agríc.. Publicado em: 2020-12

3. Calibration Strategies Applied to Laser-Induced Breakdown Spectroscopy: A Critical Review of Advances and Challenges

Over the years, laser-induced breakdown spectroscopy (LIBS) has been reported in the literature as an alternative to traditional methods of analysis, becoming well established among spectroanalytical techniques. LIBS is a technique widely used for qualitative approaches; however, it is necessary considerable effort for use in quantitative analysis, mainly du

J. Braz. Chem. Soc.. Publicado em: 2020-12

4. Open stope stability assessment through artificial intelligence

Abstract Underground mining is a set of methods that allows the extraction of ore in depth, ensuring sustainability and economic viability. One of the problems that arise in underground mine operations is open stope stability. The method for assessing stabil ity of open stopes is the stability graph proposed by Mathews et al. (1981). It is possible to estima

REM, Int. Eng. J.. Publicado em: 2020-09

5. ALTERNATIVES TO ESTIMATE THE VOLUME OF INDIVIDUAL TREES IN FOREST FORMATIONS IN THE STATE OF MINAS GERAIS, BRAZIL

ABSTRACT The objective of this study was to compare different alternatives to estimate the stem volume of individual trees in four different forest formations in the Minas Gerais state, Brazil. The data were obtained in a forest inventory procedure performed by the Minas Gerais Technological Center Foundation. The stem volumes were computed by the Smalian ex

CERNE. Publicado em: 2020-09

6. MODELING OF DRAFT AND ENERGY REQUIREMENTS OF A MOLDBOARD PLOW USING ARTIFICIAL NEURAL NETWORKS BASED ON TWO NOVEL VARIABLES

ABSTRACT Draft and energy requirements are the most important factors in the activities of farm machinery management owing to their role in matching the tractor with implements for different tillage operations. This study's aim was to model the draft and energy requirements of a moldboard plow based on two novel variables. The first was the soil texture inde

Eng. Agríc.. Publicado em: 2020-06

7. ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF PHYSIOLOGICAL AND PRODUCTIVE VARIABLES OF BROILERS

ABSTRACT Due to a number of factors involving the thermal environment of a broiler cutting installation and its interaction with the physiological and productive responses of birds, artificial intelligence has been shown to be an interesting methodology to assist in the decision-making process. For this reason, the main aim of this work was to develop an art

Eng. Agríc.. Publicado em: 2020-02

8. Prediction of restrained shrinkage crack width of slag mortar composites using data mining techniques

ABSTRACT The purpose of this study is to develop data mining models to predict restrained shrinkage crack widths of slag mortar cementitious composites. A database published by BILIR et al. [1] was used to develop these models. As a modelling tool R environment was used to apply these data mining (DM) techniques. Several algorithms were tested and analyzed u

Matéria (Rio J.). Publicado em: 25/11/2019

9. High genetic differentiation of grapevine rootstock varieties determined by molecular markers and artificial neural networks

ABSTRACT. The genetic differentiation of grapevine rootstock varieties was inferred by the Artificial Neural Network approach based on the Self-Organizing Map algorithm. A combination of RAPD and SSR molecular markers, yielding polymorphic informative loci, was used to determine the genetic characterization among the rootstock varieties 420-A, Schwarzmann, I

Acta Sci., Agron.. Publicado em: 21/10/2019

10. Modeling of tree recruitment by artificial neural networks after wood harvesting in a forest in eastern Amazon rain forest

Resumo A modelagem do recrutamento em florestais tropicais é importante para estudos de sustentabilidade do manejo florestal, por dar subsídio adequado à recuperação do estoque de madeira. O objetivo do trabalho foi estimar o recrutamento após a colheita de madeira, empregando um modelo de rede neural artificial (RNA). A área de estudo está localizad

Ciênc. Florest.. Publicado em: 30/09/2019

11. PREDICTION OF EFFICIENCY IN COLOMBIAN HIGHER EDUCATION INSTITUTIONS WITH DATA ENVELOPMENT ANALYSIS AND NEURAL NETWORKS

ABSTRACT This paper shows the results of a research of the application of data envelopment analysis (DEA) together with artificial neural networks (ANN) of higher education institutions in Colombia during the years 2011-2013, for the purpose of evaluating the technical efficiency of Colombian higher education institutions and subsequently carry out predictio

Pesqui. Oper.. Publicado em: 23/09/2019

12. Alternatives to Growth and Yield Prognosis for Pinus caribaea var. caribaea Barrett & Golfari

ABSTRACT The objective of this study was to obtain regression equations and artificial neural networks (ANNs) for prediction and prognosis of the yield of Pinus caribaea var. caribaea Barrett & Golfari. The data used for modeling comes from measuring the variables diameter at breast height (DBH) and total height (Ht) in 550 temporary plots and 14 circular pe

Floresta Ambient.. Publicado em: 12/09/2019