artificial neural network with java

... pagesdoi:10.1155/2009/243245 Research Article Doubly Periodic Traveling Waves in a Cellular Neural Network with Linear Reaction Jian Jhong Lin and Sui Sun Cheng Department of Mathematics, Tsing Hua ... in 2, we build a nonlogical neural network and showed the exactconditions such doubly periodic traveling wave solutions may or may not be generated by it The network in2 has a linear “diffusion ... any functiong, α ∈ R, δ ∈ Z and Δ, Υ, τ ∈ Z withτ, δ  1, in this paper, we will mainly be concerned with the traveling wave solutions of2.2 with velocity −δ/τ which are also spatial Υ-periodic

Ngày tải lên: 21/06/2014, 20:20

... n, khó kh n h n ó lƠ lý do tác gi ch n KHOÁN : MÔ HÌNH H I QUY TRUY N TH NG VÀ MÔ HÌNH ARTIFICIAL NEURALăNETWORK”ănh m giúp cho nhƠ đ u t l a ch n mô hình d báo t su t sinh l i thích h p v i ... sánh hai mô hình d báo t su t sinh l i ch ng khoán: Mô hình h i quy truy n th ng vƠ mô hình neural network” lƠ bƠi nghiên c u c a chính tôi Ngo i tr nh ng tài li u tham kh o đ c trích d n trong

Ngày tải lên: 24/11/2014, 01:42

... cope with such nonlinear problems, research has been underway on their identification and control using artificial neural networks based entirely on measured inputs and outputs The term artificial ... comparison purposes with the Artificial Neural Network (ANN) based controller At implementation the controllers were built using a host-target Trang 19prototyping environment with a compatible ... term artificial neural networks (ANN’s) have come to mean any architecture that has massively parallel interconnection of simple processors From a theoretical point of view, a neural network can

Ngày tải lên: 30/09/2015, 14:16

... different artificial intelligence techniques viz., Artificial Neural Networks, Particle Swarm Optimization Algorithm and Genetic Algorithms 2.1 Artificial Neural Networks Artificial neural networks ... neural network, artificial neural networks allow using simple computational operations to solve complex, mathematically ill-defined and non- linear problems One aspect of artificial neural networks ... parallelism The insensitivity of artificial neural networks to partial hardware failure is made possible only due to this aspect Another important feature of artificial neural networks is its learning

Ngày tải lên: 05/10/2015, 22:04

... component or assembly under study This paper deals with the effectiveness of wavelet-based features for fault diagnosis of a gear box using artificial neural network (ANN) and proximal support vector machines ... investigation This work deals with extraction of wavelet features from the vibration data of a bevel gear box system and classification of Gear faults using artificial neural network (ANN) and proximal ... following conditions: Good Bevel Gear, Bevel Gear with tooth breakage (GTB), Bevel Gear with crack at root of the tooth (GTC), and Bevel Gear with face wear of the teeth (TFW) for various loading

Ngày tải lên: 04/04/2016, 22:35

... training, model prediction per-formance analysis, neural network model changes and model verification 4 Neural network model For utilizing a neural network model (NNM), the prediction model has to ... model with tar calculations. Trang 6neural network model has been developed The general modellingmethodology comprises of data acquisition (measurements), mea-sured data analysis, neural network ... et al Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers Trang 7to form input and output data sets for neural network training.With various sets

Ngày tải lên: 01/08/2016, 09:32

... and inTable 2for BFB gasifiers 2.2 Artificial neural networks topology An artificial neural network is a system based on the operation of biological neural networks, a computational model inspired ... online 28 January 2013 Keywords: Biomass Gasification Artificial neural network Simulation Fluidized bed a b s t r a c t Artificial neural networks (ANNs) have been applied for modeling biomass ... with the experimental values and networks predictions 3 Results and discussion 3.1 Proposed ANN model for circulating fluidized bed gasifiers Five neural networks with seven inputs, two neurons

Ngày tải lên: 02/08/2016, 09:34

... theory and operation of artificial neural networks Trang 1818 The science of artificial neural networks is based on the neuron In order to understand the structure of artificial networks, the basic ... neural network In order to train the neural network to imitate an existing controller a vector of inputs and control targets from the controller must be collected With supervised control, a neural ... Trang 1Artificial Neural Network identification and control of the inverted pendulum Tim Callinan August 2003 Trang 33 Abstract This project takes the area of Artificial Neural Networks

Ngày tải lên: 24/09/2016, 17:26

... Civil EngineeringArtificial Neural Network (ANN) is an Artificial Intelligence technique which is believed to have broad applications in risk management [8] McKim used the neural network for identifying ... projects The following sections will explain the research approach in detail 2 Artificial Neural Network Artificial Neural Network (ANN) is an information processing technology that simulates the hu-man ... layer A neural network may consist of two or more layers which are named as input, output and hidden layers That means that a neural network may or may not have hidden layers In neural network,

Ngày tải lên: 11/02/2020, 12:51

... www.GrowingScience.com/ijiec Modeling and optimization of laser direct structuring process using artificial neural network and response surface methodology Institute for Factory Automation and Production ... the quality of the final product In this work we develop mathematical models by using Artificial Neural Network (ANN) and Response Surface Methodology (RSM) to study this process The proposed ... Growing Science Ltd All rights reserved Keywords: LDS process MID process Modeling Artificial neural network Response surface methodology 1 Introduction The MID process has received great

Ngày tải lên: 14/05/2020, 21:53

... Another predictive model based on ANN (Artificial neural network) is employed, and the experimental results are compared with it and also with RSM model The neural network is constructed using the ... influenced with feed and a negative trend was observed with approaching angle, speed and depth of cut The neural network model for Ra predicted with moderate accuracy Cutting force (Fc) increased with ... force Risbood et al (2003) found that, using neural network, surface finish could be predicted within a reasonable degree of accuracy in turning with TiN coated tools Suresh et al., (2002) developed

Ngày tải lên: 14/05/2020, 22:03

... signal to m succeeding neurons Trang 9Artificial Neural Network Organized into layers of neurons  Typically 3 or more: input, hidden and output  Neural networks are made up of nodes or units, ... Simplified (binary) artificial neuron Trang 11 Simplified (binary) artificial neuron with weights Trang 12 Simplified (binary) artificial neuron; no weights Trang 13 Simplified (binary) artificial ... ComputationTrang 59BackpropagationTrang 60 Training a Neural Network via Gradient Descent with Backpropagation Trang 61Training a Neural Network

Ngày tải lên: 15/05/2020, 22:34

... samples Abbreviations ANN: Artificial neural network; CV: Cross validation; GRRANN: Gene regulatory network-based regularized artificial neural network; GRN: Gene regulator network; MLP: Multi layer ... in avoiding overfitting To this end, we design a gene regulatory network based artificial neural neu-ral network model together with regularization methods for simultaneous shrinkage of gene-sets ... gives stable performance estimates across independent test sets Keywords: Artificial neural network, Gene regulatory networks, Prediction of response, Clinical trial, Group Lasso Background One

Ngày tải lên: 25/11/2020, 16:43

... signal to m succeeding neurons Trang 9Artificial Neural Network Organized into layers of neurons  Typically 3 or more: input, hidden and output  Neural networks are made up of nodes or units, ... Simplified (binary) artificial neuron Trang 11 Simplified (binary) artificial neuron with weights Trang 12 Simplified (binary) artificial neuron; no weights Trang 13 Simplified (binary) artificial ... ComputationTrang 59BackpropagationTrang 60 Training a Neural Network via Gradient Descent with Backpropagation Trang 61Training a Neural Network

Ngày tải lên: 17/05/2021, 11:13

... ship berthing using artificial neural network, some new ideas are proposed in this research Firstly, head-up coordinate system is suggested to consider two new inputs for neural controller, a ... System Engineering Van-Suong Nguyen Trang 3A StudyonAn AutomaticShip Berthing Based on Artificial Neural Network Controller Using Head-up Coordinate System Supervisor Prof NamkyunIm By Van-Suong ... National Maritime University August 2016 Trang 4A StudyonAn AutomaticShip Berthing Based on Artificial Neural Network Controller Using Head-up Coordinate System A Dissertation by Van-Suong Nguyen

Ngày tải lên: 18/05/2021, 22:42

... reaction time, on the removal efficiency of AR17 were studied For the first time, an artificial neural network (ANN) model with five neurons at the input layer, 14 layers in the hidden layer, and one ... removal of AR17, an artificial neural network (ANN) was utilized ANN is a mathematical algorithm that can generate a relation between independent and dependent parameters of a process without requiring ... heterogeneous Fenton process with Fe-NP-Clin promotes the overall phytotoxicity reduction of the solution under the applied operational conditions 2.3 Artificial neural network modeling of a heterogeneous

Ngày tải lên: 13/01/2022, 00:00

... square root of the MSE 2.4 ANN model development Artificial neural network (ANN) is computing systems dubiously inspired by the biological neural networks that create animal brains An ANN is based ... the neural network model is that it can model efficiently different response surfaces Neural networks are very flexible models and have a tendency to overfit data The main disadvantage of a neural ... [44,45] In this work, we used a typical feed-forward neural network with an error back-propagation learning algorithm to train it This neural network style propagates information in the feed-forward

Ngày tải lên: 25/10/2022, 13:17

... parameters of the neural network model, so another test subset is needed only to assess the performance of a trained neural network, viz., the whole dataset is divided into three subsets with different ... 2 first dimension of the new basis Figure 1. Geometric Illustration of PCA 4 Forward Neural Network Neural networks are widely used in pattern classification since they do not need any information ... the a priori probabilities of different classes A two-hidden-layer backpropagation neural network is adopted with sigmoid neurons in the hidden layers and linear neuron in the output layer via

Ngày tải lên: 01/11/2022, 09:43

... for the discrete-time MAM neural network 2 Discrete-Time MAM Neural Network Model and Some Notations In this section we formulate a discrete-time MAM neural network model with time-varying delays ... equilibrium point of the discrete-time MAM neural network2.7 is global exponential stable 4 An Example Consider the following discrete-time MAM neural network with three fields: x11n 1  I11 α11x11n ... memory neural network,” Neural Processing Letters, vol 35, pp 187– 202, 2012 8 S Mohamad, “Global exponential stability in continuous-time and discrete-time delayed bidirectional neural networks,”

Ngày tải lên: 02/11/2022, 10:40

... system, K-means and K-medians clustering of the classical approach and Kohonen network of the artificial neural network approach The system is applied to ETM + images of an area North to Mosul ... classical approach is K-means clustering algorithm [3] while Kohonen network is the most commonly used one of the artificial neural network approach [4] So far many research works have conducted to ... by using initial learning rate of 0.7 with a decrement of (0.7/500) at each next cycle where the number of cycles is taken to be 500 Kohonen neural network with this structure is supposed to be

Ngày tải lên: 02/11/2022, 11:36