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This study proposes on the prediction and classification of Diabetes Mellitus using Artificial Neural Network (ANN) and hybrid Adaptive Neuro-Fuzzy Inference System (ANFIS). The network was trained by using the data of 100 individuals with mean age of 42 years with an equal proportion of male and female. The performance of each approach is further discussed on the basis of accuracy and validates accurate...
Recurrent neural network (RNN) — based approach to identification of underwater robot (UR) is considered and investigated in the paper. It was shown that RNN models can be successfully trained to nonlinear behaviour of a UR. Experiments carried out with data taken from UR dynamics model also confirmed effectiveness and prospective of the approach considered.
This paper presents a modeling technique of sequential batch reactor (SBR) for aerobic granular sludge (AGS) using artificial neural network (ANN). A SBR fed with synthetic wastewater was operated at high temperature of 50˚C to study the formation of AGS for simultaneous organics and nutrients removal in 60 days. The feed forward neural network (FFNN) was used to model the nutrients removal process...
This paper presents an approach to digit recognition using single layer neural network classifier with Principal Component Analysis (PCA). The handwritten digit recognition is an important area of research as there are so many applications which are using handwritten recognition and it can also be applied to new application. There are many algorithms applied to this computer vision problem and many...
Combustion process in utility boiler is very complicated and not fully understood until now. One operating challenge in boiler operation is the unreliable oxygen sensor could result in flame extinction of burners. An on-line virtual sensor is desirable for the unreliable oxygen sensor. This work elaborates how to build a Neural Network-based oxygen virtual sensor by make full use of the mass data...
With the advent of advanced diesel after-treatment technologies, select catalyst reduction(SCR) becomes dominant technology for the new emission legislation in china. Because of sophisticated NOx sensors are becoming a critical cost challenge to OEMs, open loop SCR is mainly used at present, and which lead to be difficultly adaptive to control emission reduction and calibration workload was heavy...
The horizontal well is a very complex issue, only two situations considered, which are homogeneous and dual media infinite formation in the paper. According to self-organization, self-learning and adaptive characteristics of neural network, mathematical models built, then BP neural network classifier model constructed in order to recognize horizontal well testing parameters, at last, one example on-site...
The paper proposes a novel neuron model termed as Generalized Power Mean Neuron model (GPMN). The paper focuses on illustrating the computational power and the generalization capability of this model. In this model, the aggregation function is based on generalized power mean of the inputs. The performance of the neural network using GPMN model is compared with traditional feed-forward neural network...
X-ray real-time digital imaging technique is applied in getting log image without log destruction. This paper presents the average density value of the specific spot of log is measured quickly and exactly according to log perimeter and log image information using the method of artificial neural network. According to the basic knowledge of X-ray testing technique, the method of getting high quality...
According to the chromaticity theory, the computer vision system used in color quantitative measurement was developed, which was marked by the 1980A color luminance meter. Munsell color system is selected to establish the mutual conversion between RGB and L*a*b* color model for camera, the conversion relation between RGB color space of CCD camera and L*a*b* color space under a big color gamut was...
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