Application of RBF neural network improved by peak density function in intelligent color matching of wood dyeing

Guan, Xuemei; Zhu, Yuren; Song, Wenlong

doi:10.1016/j.chaos.2016.02.015

Cited by 19 publications

(11 citation statements)

References 13 publications

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“…The RBFNN are a type of artificial neural networks (ANN) that calculate the output as a function of distance from a point called center. The basic topology of RBFNN comprises an input layer, a hidden layer and an output layer formed by linear processing units (Arliansyah & Hartono, 2018;Guan, Zhu, & Song, 2016;Gubana, 2018). A typical RBFNN configuration is shown in Figure 1 for a single output, where the outputs of the nonlinear activation are combined linearly with the weight vector β of the output layer to produce the network.…”

Section: Methodsmentioning

confidence: 99%

“…Where X ϵ Rⁿ is an input vector, ϕi is the basis function of the network from Rⁿ to R, wi are weights of the network is called the center vector of the i-th node is called the bandwidth vector of the i-th node denotes the Eucliden node. The training of RBF neural network is accomplished through the estimation of three kinds of parameters, namely the centers and the widths of the radial basis functions and the neuron connection weights (Guan et al, 2016). RBFNN networks form a special architecture of neural networks that present important advantages compared to other neural network types, including simpler structure and faster learning algorithms (Moody and Darken, 1988, Darken and Moody, 1990and Binchini et al, 1995.…”

Section: Methodsmentioning

confidence: 99%

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Classification of Adolescent Offenders of the Law with Radial Neural Network Bases Function

Vera¹,

López²,

Lópera³

et al. 2019

MAS

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Radial Basis Function Neural Networks (RBFNN) are a type of artificial neuronal network (ANN) that estimate the output of the function taking as a reference the distance to a point called center. This paper presents a RBFNN for the classification of adolescents' offenders of the law according to their dangerousness level, that have been admitted to the Specialized Attention Center (SAC), "El Redentor" in Bogotá, Colombia in the year 2017. This classification may be utilized by psychosocial teams of the SAC in order to customize and make more effective the therapeutic pedagogical treatment. The ANN developed is particularly good for identifying adolescents with a high, low and null dangerousness level.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Classification of Adolescent Offenders of the Law with Radial Neural Network Bases Function

Vera¹,

López²,

Lópera³

et al. 2019

MAS

View full text Add to dashboard Cite

show abstract

“…Although the structure of the Radial Basis Function (RBF) neural network is rather simple, the network has a strong generalization ability [23,24]. The RBF neural network has shown a good classification and approximation performance in various applications [25,26]. As shown in Figure 2, the estimated output is a weighted summation utilizing the following equation:…”

Section: Multilayer Perceptron (Mlp) Networkmentioning

confidence: 99%

A Multidisciplinary Approach for Evaluating Spatial and Temporal Variations in Water Quality

Quan

Loc

et al. 2019

Water

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The primary goal of this study is to investigate the classification capability of several artificial intelligence techniques, including the decision tree (DT), multilayer perceptron (MLP) network, Naïve Bayes, radial basis function (RBF) network, and support vector machine (SVM) for evaluating spatial and temporal variations in water quality. The application case is the Song Quao-Ca Giang (SQ-CG) water system, a main domestic water supply source of the city of Phan Thiet in Binh Thuan province, Vietnam. To evaluate the water quality condition of the source, the government agency has initiated an extensive sampling project, collecting samples from 43 locations covering the SQ reservoir, the main canals, and the surrounding areas during 2015–2016. Different classifying models based on artificial intelligence techniques were developed to analyze the sampling data after the performances of the models were evaluated and compared using the confusion matrix, accuracy rate, and several error indexes. The results show that machine-learning techniques can be used to explicitly evaluate spatial and temporal variations in water quality.

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“…Of all neural networks (NN), the three-layer RBF and its variants, like PNN, GRNN, CPN, etc., have become famous due to limited network parameters and reliability in giving output results. The RBF is one of the neural network tools [28] that is a feed-forward with three layers, one is input, the other is hidden or known as a radial basis layer, the last is the output layer. Figure 2 shows the block diagram of the RBF.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

A Parametric Study on Control of Flow Separation Over an Airfoil in Incompressible Regime

Prabhu

Srinivas

2018

IIUMEJ

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This paper presents the effects of airfoil geometry on flow separation behavior and obtains the transition patterns at a specific angle of attack. A strong adverse pressure gradient field is observed at the leading edge of the airfoil, and it results in a flow detachment. Leading edge flow separation is studied along with the variation of skin friction coefficient over the airfoil. Novelty in the approach is the development of a hybrid control scheme to delay the flow separation with blowing/suction of air (termed active control) over the airfoil together with the tapping of flow from the pressure side as in a classical passive control procedure. The active controller delays the flow separation, while the passive controller is used to reduce the drag coefficient significantly and increases the total performance of an airfoil. The effectiveness of these controls is examined by varying the control parameters including blowing/suction velocity, the position of the slot in terms of percentage of chord and size of the slot. All the numerical simulations are carried out using ANSYS-Fluent software. A surrogate model is also developed to predict the aerodynamic characteristics conveniently without much computational effort. The outcome of this study reveals that the blowing/suction velocity has a higher influence in delaying the flow separation. ABSTRAK: Kertas ini membentangkan tentang kesan geometri aerofoil pada perubahan pemisah aliran udara dan memperoleh bentuk peralihan pada darjah yang tepat. Terdapat tekanan kuat yang tidak sesuai pada kawasan kecerunan di hujung hadapan permukaan aerofoil, dan ini menyebabkan aliran udara terpisah. Pemisah aliran udara pada hujung hadapan ini dikaji bersama koefisien geseran pada permukaan aerofoil. Pendekatan baru pada kaedah ini adalah berkaitan pembangunan skim kawalan hibrid bagi melengahkan aliran pemisah udara melalui tiupan/sedutan udara (kawalan aktif) ke atas aerofoil bersama ketukan pada aliran dari tepi tekanan seperti mana prosedur klasik kawalan pasif. Kawalan aktif ini melengahkan aliran pemisah udara, sebaliknya kawalan pasif telah digunakan bagi mengurangkan koefisien penangguhan dengan ketara dan menambahkan jumlah prestasi aerofoil. Keberhasilan kawalan-kawalan ini dikaji dengan mengubah parameter kawalan termasuk kelajuan tiupan/sedutan udara, posisi slot berdasarkan peratusan garis temu dan saiz slot. Semua simulasi-simulasi numerikal ini dijalankan menggunakan perisian Ansys-Fluent. Model pengganti turut dibangunkan untuk menjangka ciri-ciri aero-dinamik dengan mudah tanpa usaha pengiraan yang banyak. Keputusan kajian ini mendedahkan tentang kelajuan tiupan/sedutan udara berpengaruh besar dalam melambatkan pemisahan aliran udara.

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Application of RBF neural network improved by peak density function in intelligent color matching of wood dyeing

Cited by 19 publications

References 13 publications

Classification of Adolescent Offenders of the Law with Radial Neural Network Bases Function

Classification of Adolescent Offenders of the Law with Radial Neural Network Bases Function

A Multidisciplinary Approach for Evaluating Spatial and Temporal Variations in Water Quality

A Parametric Study on Control of Flow Separation Over an Airfoil in Incompressible Regime

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