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| Registros recuperados: 22 | |
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| Aboukarima,Abdulwahed; El-Marazky,Mohamed; Elsoury,Hussien; Zayed,Moamen; Minyawi,Mamdouh. |
| 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 grading and classification of Egyptian faba-bean seeds, covering five varieties: Giza3, Giza461, Misr1, Nobarya1, and Sakha1. Fifteen seed morphological features were then calculated, and artificial neural networks classified faba beans into different varieties. The results indicated an overall classification accuracy of 77.5% was achieved in training phase and it was 100% when testing dataset was used.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Faba bean; Quality; Classification; Artificial neural network; Features. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000600791 |
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| Murta Jr.,L.O.; Ruiz,E.E.S.; Pazin-Filho,A.; Schmidt,A.; Almeida-Filho,O.C.; Simões,M.V.; Marin-Neto,J.A.; Maciel,B.C.. |
| The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Artificial neural network; Color kinesis images; Left ventricular function. |
| Ano: 2006 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2006000100001 |
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| SANUSI, Mayowa Saheed; Akinoso, Rahman. |
| This study was designed to evaluate and model the impacts of processing parameters (steaming time, soaking time, paddy moisture content and soaking temperature) on the energy consumption of five rice varieties (NERICA 8, FARO 52, FARO 61, FARO 60 and FARO 44). Energy consumption in the cleaning, soaking, steaming, drying, dehusking, polishing and grading operations were estimated by fitting data on labour, fuel and electricity consumption, time and machine efficiency into standard equations to determine total energy consumption. The energy consumptions were separately modelled using Taguchi and Artificial Neural Network (ANN) techniques for each rice variety. The accuracy of models was determined using the coefficient of determination (R2) and Mean Square... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Artificial neural network; Energy Consumption; Modelling; Rice varieties; Taguchi. |
| Ano: 2022 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/7235 |
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| Al-Janobi,Abdulrahman; Al-Hamed,Saad; Aboukarima,Abdulwahed; Almajhadi,Yousef. |
| 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 index (STI), which was formed from the clay, sand, and silt contents with a range of 0.03–0.84. The second variable was the field working index (FWI), formed by combining the plow width, plowing speed, soil bulk density, soil moisture content, plowing depth, and tractor power into one dimensionless variable, which had a range of 7.17–82.45. The coefficient of determination (R2) values obtained using a... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil texture index; Field working index; Artificial neural network; Prediction; Tillage. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000300363 |
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| Amiri Chayjan, Reza; Kaveh, Mohammad; Khayati, Sasan. |
| The effect of air temperature, air velocity and infrared (IR) radiation on the drying kinetics of sour cherry was investigated using a laboratory infrared dryer. Experiments were conducted at air temperatures of 35, 50 and 65°C, air velocities of 0.5, 1.1 and 1.7 m/s and IR radiations of 500, 1,000 and 1,500 W. Five empirical drying models for describing time dependence of the moisture ratio change were fitted to experimental data. Artificial neural network (ANN) method was used to predict the effective moisture diffusivity and specific energy consumption of the samples. Among the applied models, Midilli et al. model was the best to predict the thin layer drying behavior of sour cherry. Effective moisture diffusivity of sour cherry varied between... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Sour cherry; Drying; Effective moisture diffusivity; Activation energy; Artificial neural network. |
| Ano: 2014 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2552 |
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| Eyng,Eduardo; Silva,Flávio Vasconcelos da; Palú,Fernando; Fileti,Ana Maria Frattini. |
| Gaseous ethanol may be recovered from the effluent gas mixture of the sugar cane fermentation process using a staged absorption column. In the present work, the development of a nonlinear controller, based on a neural network inverse model (ANN controller), was proposed and tested to manipulate the absorbent flow rate in order to control the residual ethanol concentration in the effluent gas phase. Simulation studies were carried out, in which a noise was applied to the ethanol concentration signals from the rigorous model. The ANN controller outperformed the dynamic matrix control (DMC) when step disturbances were imposed to the gas mixture composition. A security device, based on a conventional feedback algorithm, and a digital filter were added to the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Absorption column; Artificial neural network; Feedforward control. |
| Ano: 2009 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132009000400020 |
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| Ferraz,Patricia Ferreira Ponciano; Yanagi Junior,Tadayuki; Hernández Julio,Yamid Fabián; Castro,Jaqueline de Oliveira; Gates,Richard Stephen; Reis,Gregory Murad; Campos,Alessandro Torres. |
| The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Animal welfare; Artificial neural network; Broiler; Modeling; Neuro-fuzzy network; Thermal comfort. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2014000700559 |
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| Tedesco,Leonel P. C.; Freitas,Adriano da C. de; Molz,Rolf F.; Schreiber,Jacques N. C.. |
| ABSTRACT This article proposes an automatic method for classification of cured tobacco leaves. Typically this process is performed manually, allowing the occurrence of human errors. In addition, the existence of an automated comparative procedure, helping to perform the classification, can make this process faster and more transparent. In order to implement the method, non-invasive to the agricultural product, 250 samples of Virginia tobacco digital images in the RGB and HSV color models were analyzed. The validation of the method was carried out using partial least squares (PLS) and artificial neural network (ANN), presenting a qualitative and quantitative analysis of both tools. It has been verified that the PLS can be applied to this method, as it has a... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Image processing; Partial least square; Artificial neural network. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001000782 |
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| Chen,Fudi; Li,Hao; Xu,Zhihan; Hou,Shixia; Yang,Dazuo. |
| Background In the field of microbial fermentation technology, how to optimize the fermentation conditions is of great crucial for practical applications. Here, we use artificial neural networks (ANNs) and support vector machine (SVM) to offer a series of effective optimization methods for the production of iturin A. The concentration levels of asparagine (Asn), glutamic acid (Glu) and proline (Pro) (mg/L) were set as independent variables, while the iturin A titer (U/mL) was set as dependent variable. General regression neural network (GRNN), multilayer feed-forward neural networks (MLFNs) and the SVM were developed. Comparisons were made among different ANNs and the SVM. Results The GRNN has the lowest RMS error (457.88) and the shortest training time (1... |
| Tipo: Journal article |
Palavras-chave: Artificial neural network; Fed-batch fermentation; General regression neural network; Iturin A; Support vector machine. |
| Ano: 2015 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582015000400003 |
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| Registros recuperados: 22 | |
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