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Modeling Hyperspectral Response of Water-Stress Induced Lettuce Plants Using Artificial Neural Networks
(Mdpi, 2019-12-01)
Modeling the hyperspectral response of vegetables is important for estimating water stress through a noninvasive approach. This article evaluates the hyperspectral response of water-stress induced lettuce (Lactuca sativa ...
Plantar Pressure Measurement System with Improved Isolated Drive Feedback Circuit and ANN: Development and Characterization
(2020-10-01)
The use and development of plantar pressure measurement systems (PPMs) have increased in recent years, in order to understand and objectively evaluate the interaction between the feet and the support surfaces. The PPMs are ...
Hydrolysis of lactose: estimation of kinetic parameters using Artificial Neural Networks
(David Publishing, 2013-10-20)
The analysis of any kinetic process involves the development of a mathematical model with predictive purposes. Generally, those models have characteristic parameters that should be estimated experimentally. A typical example ...
A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened Steel turning
(Abcm Brazilian Soc Mechanical Sciences & Engineering, 2010-12-01)
The use of artificial neural networks for prediction in hard turning has received considerable attention in literature. An often quoted drawback of ANNs is the lack of a systematic way for the design of high performance ...
Detecting attacks to computer networks using a multi-layer perceptron artificial neural network
(The International Journal of Forensic Computer Science, 2012)
Are northeast and western Himalayas earthquake dynamics better “organized” than Central Himalayas: An artificial neural network approachAre northeast and western Himalayas earthquake dynamics better “organized” than Central Himalayas: An artificial neural network approach
(Instituto de Geofísica, 2010)
A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened steel turning
(2010-01-01)
The use of artificial neural networks for prediction in hard turning has received considerable attention in literature. An often quoted drawback of ANNs is the lack of a systematic way for the design of high performance ...
Forest-Genetic method to optimize parameter design of multiresponse experiment
(2020-08-27)
We propose a methodology for the improvement of the parameter design that consists of the combination ofRandom Forest (RF) with Genetic Algorithms (GA) in 3 phases: normalization, modelling and ...
Application of artificial neural networks in the prediction of sugarcane juice Pol
(Univ Federal Campina Grande, 2019-01-01)
Innovative techniques that seek to minimize the costs of production and the laboriousness of certain operations are one of the great challenges in the sugar-energy sector nowadays. Thus, the objective of the present study ...
Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays
(Pergamon-Elsevier B.V. Ltd, 2012-07-01)
This work presents a study on the applicability of radial base function (RBF) neural networks for prediction of Roughness Average (R-a) in the turning process of SAE 52100 hardened steel, with the use of Taguchi's orthogonal ...