... https://en.wikipedia.org/wiki/Artificial_neural_network • https://en.wikipedia.org/wiki/Evolutionary_algorithm • ANN, EA : Aforge.Net documents • Dr Saceed Shiry, Intelligent Decision-Making Support Systems ... cấu hình game ArcheAge • Cấu hình đề nghị: • Hệ điều hành: 32-bit hoặc 64-Bit Windows XP SP3, Vista SP1, Win7 SP1, Win8/8.1 Trang 6Đồ họa• Chuyển động nhân vật • Hình ảnh nhân vật và môi trường ... 19Xây dựng csdl• Dữ liệu thu thập được lưu trữ vào cơ sở dữ liệu và được phân thành tập Training và tập Testing với tỷ lệ 7/3 • Trang 20Quá trình huấn luyệnTrang 21Kiểm thửTrang 22Ứng dụngTrang 24Tài
Ngày tải lên: 24/08/2015, 22:46
... of different neural network modelling approaches. Model inputs Fuel flow Total fuel supplied (from beginning) (kg) Fuel supplied in the last 10 min (kg) Fuel supplied in the last 10 min (kg) Fuel ... char, ash and minor contaminates) called ‘‘syngas’’, using gasifying agents[1] H2and CO contain only around 50% of the energy in the gas while the remained energy is contained in CH4 and higher ... be found in the case where the process tem-perature progression (desired output data in neural network training procedure) is function (Eq (7)) of fuel and air injected in the last 10 min together
Ngày tải lên: 01/08/2016, 09:32
Artificial neural network models for biomass gasification in fluidized bed gasifiers
... on artificial neural networks is that it does not require the mathematical description of the phenomena involved in the process, and might therefore prove useful in simulating and up-scaling ... these input and output variables, obtained from published experimental data, are shown in Table 1for CFB gasifiers and inTable 2for BFB gasifiers 2.2 Artificial neural networks topology An artificial ... necessary to take into account that in this case eight inputs are considered as shown in Eq.(4): The relative influence of the input variables was also evaluated using Eq.(3) as in the CFB gasifiers’
Ngày tải lên: 02/08/2016, 09:34
Response surface and artificial neural network prediction model and optimization for surface roughness in machining
... prediction models using artificial neural network (ANN) during turning of free machining steel and reported that the cutting speed and feed rate had significant effects in reducing the surface roughness, ... machining mild steel using RSM with TiN-coated WC cutting tools It was found that, the surface roughness was decreased with an increase in cutting speed and increased as feed elevated An increase ... roughness in machining AISI 1030 steel using coated carbide tool (TiC/ Al2O3/TiN) Feed rate and insert nose radius were main influencing factors on the surface roughness Depth of cut was not more informative
Ngày tải lên: 14/05/2020, 22:03
Application of signal processing tools and artificial neural network in diagnosis of power system faults
... presently Associate Professor in the Electrical Engineering Department of Narula Institute of Technology, Kolkata, India She has obtained her graduation in Electrical Engineering from B.E College, Shibpur, ... Degree level and as an administrator (acting principal) at the diploma engineering level, since 2004 She has also served as HOD, Electrical Engineering Department at Narula Institute of Technology ... faulty phase is used for training the BPNN for obtaining the fault location All the power system networks involved in the study have been simulated in MATLAB Simulink environ- ment The feature
Ngày tải lên: 29/12/2022, 10:40
Load shedding in power system using the ahp algorithm and artificial neural network
... (trainbr) training algorithm: Trainbr is an ANN training function that allows updating weight and threshold values It minimizes the combination of squaring and weighting errors, and then determines ... to shedding the load are put into a data set to train the neural network The results were a data set consisting of 122 samples During neural network training, the data set is divided into 80% ... of the training methods are presented in Table 8 and Figure 6 Fig 5: ANN configuration Trang 8Table 8 Training and test accuracy of Artificial Neural Network training methods Training algorithm
Ngày tải lên: 18/02/2023, 08:20
So sánh hai mô hình dự báo tỷ suất sinh lời chứng khoán. Mô hình hồi quy truyền thống và mô hình Artificial Neural Network
... 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 t ng đi u ki n c th và có nh ng quy t đ nh kinh t h p lý Trang 122 ... Pricing Model) đ c ba nhƠ nhƠ kinh t h c William Sharpe, John Lintner vƠ Jack Treynor đ a ra vƠo nh ng n m gi a th p niên 60 Mô hình CAPM (Capital Asset Pricing Model) nh m d báo t su t sinh ... th n kinh nh sau: D a trên ý ngh a kinh t c a các bi n nh đư trình bƠy m c d li u, tác gi s d ng 5 bi n kinh t làm d li u trong m u đ xây d ng mô hình m ng th n kinh nhân t o d báo t su t sinh
Ngày tải lên: 24/11/2014, 01:42
Artificial neural network based adaptive controller for DC motors
... '/Gain3' * * Regarding '/Gain3': * Gain value: rtP.Gain3_Gain */ rtB.Gain3 = rtB.Gain1_a * rtP.Gain3_Gain; /* Gain: '/Gain4' * * Regarding '/Gain4': * Gain value: rtP.Gain4_Gain */ rtB.Gain4 ... Gain: '/Gain1' * * Regarding '/Gain1': * Gain value: rtP.Gain1_b_Gain */ rtB.Gain1_b[0] = rtB.Reciprocal_a[0] rtP.Gain1_b_Gain; rtB.Gain1_b[1] = rtB.Reciprocal_a[1] rtP.Gain1_b_Gain; rtB.Gain1_b[2] ... Regarding '/Gain': * Gain value: rtP.Gain_b_Gain */ rtB.Gain_b[0] = rtB.netsum_a[0] rtP.Gain_b_Gain; rtB.Gain_b[1] = rtB.netsum_a[1] rtP.Gain_b_Gain; rtB.Gain_b[2] = rtB.netsum_a[2] rtP.Gain_b_Gain;
Ngày tải lên: 30/09/2015, 14:16
Evolution of artificial neural network controller for a boost converter
... 18Chapter 1 Introduction Artificial intelligent techniques have started replacing the conventional techniques for many different applications In control engineering, artificial neural network (ANN) ... different artificial intelligence techniques viz., Artificial Neural Networks, Particle Swarm Optimization Algorithm and Genetic Algorithms 2.1 Artificial Neural Networks Artificial neural networks ... one direction from input to output The network is trained in a supervised fashion involving both network inputs and target outputs The algorithms proposed for training and designing the architecture
Ngày tải lên: 05/10/2015, 22:04
fault dialogis of spur gear box using artificial neural network
... principle of risk minimization In artificial neural network (ANN) traditional Empirical Risk Minimization (ERM) is used on training data set to minimize the error But in SVM, Structural Risk Minimization ... Malfunctions in machinery are often sources of reduced productivity and increased maintenance costs in various industrial applications For this reason, machine condition monitoring is being pursued ... using J48 algorithm and the predominant features were fed as input for training and testing ANN and PSVM and their relative efficiency in classifying the faults in the bevel gear box was compared
Ngày tải lên: 04/04/2016, 22:35
Artificial Neural Network Identification And Control Of The Inverted Pendulum
... Supervised learning uses an existing controller or human feedback in training the neural network In order to train the neural network to imitate an existing controller a vector of inputs and control ... processing 3 Artificial neural networks (ANN) have memory The memory in neural networks corresponds to the weights in the neurons Neural networks can be trained offline and then transferred into ... disturbance occurs in the system Direct inverse control does not require an existing controller in training A neural network is trained to model the inverse of the process The neural network is cascaded
Ngày tải lên: 24/09/2016, 17:26
A risk assessment framework for construction project using artificial neural network
... broad applications in risk management [8] McKim used the neural network for identifying risks [9] Wenxi used back-propagation neural network for assessing risks in highway projects in China [10] In ... 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 brain ... Technology in Civil Engineering Artificial Neural Network (ANN) is an Artificial Intelligence technique which is believed to have broad applications in risk management [8] McKim used the neural network
Ngày tải lên: 11/02/2020, 12:51
Modeling and optimization of laser direct structuring process using artificial neural network and response surface methodology
... Trang 1International Journal of Industrial Engineering Computations 6 (2015) 553–564Contents lists available at GrowingScience International Journal of Industrial Engineering Computations ... Computations homepage: www.GrowingScience.com/ijiec Modeling and optimization of laser direct structuring process using artificial neural network and response surface methodology Institute for Factory ... for producing the fine circuit line/space as well as the high quality and reliability for the MID structure Artificial Neural Network (ANN) as well as the RAM methods have been used in different
Ngày tải lên: 14/05/2020, 21:53
Bài giảng Máy học nâng cao: Artificial neural network - Trịnh Tấn Đạt
... weights Trang 15Introducing Bias Perceptron needs to take into account the bias o Bias is just like an intercept added in a linear equation. o It is an additional parameter in the Neural Network which ... (binary) artificial neuron with weights Trang 12 Simplified (binary) artificial neuron; no weights Trang 13 Simplified (binary) artificial neuron; add weights Trang 14 Simplified (binary) artificial ... of computing power Neural networks are designed to be massively parallel The brain is effectively a billion times faster Trang 5Applications of neural networksTrang 6Medical Imaging Trang
Ngày tải lên: 15/05/2020, 22:34
Forecasting exports and imports through artificial neural network and autoregressive integrated moving average
... 2.1 Artificial Neural Network Artificial Neural Network (ANN) is a well-organized data mining technique which is achieved from a biological neural networks ANN collects a large amount of data interconnected ... (2010, August) Energy demand estimation of China using artificial neural network In Business Intelligence and Financial Engineering (BIFE), 2010 Third International Conference on (pp 32-34) IEEE ... Growing Sci © Keywords: Artificial Neural Networks (ANN) Autoregressive Integrated Moving Average (ARIMA) Forecasting Export and Import Kingdom of Saudi Arabia 1 Introduction The Kingdom
Ngày tải lên: 26/05/2020, 22:37
A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data
... consist of two independent clinical trial datasets In each panel, the left end points indicate the model performance in CV trained on the indicated training set and the right endpoints indicate the ... approach for tracking robustness against variations in training data More specifically, the training data was sampled with replacement to generate 100 new training sets The ANN was then trained on each ... support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation
Ngày tải lên: 25/11/2020, 16:43
Bài giảng Artificial neural network
... weights Trang 15Introducing Bias Perceptron needs to take into account the bias o Bias is just like an intercept added in a linear equation. o It is an additional parameter in the Neural Network which ... (binary) artificial neuron with weights Trang 12 Simplified (binary) artificial neuron; no weights Trang 13 Simplified (binary) artificial neuron; add weights Trang 14 Simplified (binary) artificial ... of computing power Neural networks are designed to be massively parallel The brain is effectively a billion times faster Trang 5Applications of neural networksTrang 6Medical Imaging Trang
Ngày tải lên: 17/05/2021, 11:13
SDH TS 00044 a study on an automatic ship berthing based on artificial neural network controller using head up coordinate system
... automatic 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, ... Automatic Ship Berthing Based on Artificial Neural Network Controller Using Head-up Coordinate System Van-Suong Nguyen Department of Maritime Transportation System Engineering, Graduate School ... Artificial Neural Network (ANN) has been known as one of most effective theories for automatic ship berthing because it has the learning ability and mimics action of human’s brain in performing
Ngày tải lên: 18/05/2021, 22:42
Heterogeneous Fenton-like degradation of Acid Red 17 using Fe-impregnated nanoporous clinoptilolite: artificial neural network modeling and phytotoxicological studies
... Fe-NP-Clin are similar to those in the NP-Fe-NP-Clin sample, indicating that the NP-Fe-NP-Clin surface functional groups were not altered significantly during the impregnation process However, the intensity ... Fe-complexes such as Fe-binuclear complex in internal and external NP-Clin framework.12,27 Trang 6Table 2 Microstructural characteristics of NP-Clin and Fe-NP-Clin.Fe-NP-Clin NP-Clin Specific surface ... the data (Yi) , containing the training, validation, and test sets, were scaled to a new value Ynorm using Eq (13).17,20 Y norm= 2( Y i − Y i,min Y i,max − Y i,min where Yi,min and Yi,max are the
Ngày tải lên: 13/01/2022, 00:00
QSPR MODELLINGOF STABILITY CONSTANTS OF METAL THIOSEMICARBAZONE COMPLEXESUSING MULTIVARIATE REGRESSIONMETHODSAND ARTIFICIAL NEURAL NETWORK
... regression [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 ... 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 on a collection ... trained network was verified by determining the error between the predicted value and the real value All the data of the patterns were normalized to be less than 1 before training the neural network;
Ngày tải lên: 25/10/2022, 13:17