artificial neural network models of sports motions

... analyze and control the performance of the (LDS) process and the quality of the final product In this work we develop mathematical models by using Artificial Neural Network (ANN) and Response Surface ... speed of 1900 mm/s and laser frequency of 79 kHz and the second laser power of 9 W, laser speed of 2200 mm/s and laser frequency of 78 kHz The first parameters group gives a groove depth of 11,7 ... results of the ANN model, the high Ra of 5 µm can achieved by the sets of the laser parameters shown in Table 5 a Ra at laser power of 3 and 9 (W) b Interactive width at laser power of 3 and

Ngày tải lên: 14/05/2020, 21:53

... Fenton-like process and investigate the effect and importance of different operational variables on the removal of AR17, an artificial neural network (ANN) was utilized ANN is a mathematical algorithm ... one of the main advantages of this process 2.2.2 Effect of the initial H2O2 concentration Figure 5c indicates the changes in the removal efficiency of AR17 by changing the initial concentration of ... optimum conditions for maximum removal of 20 mg/L AR17 at 180 min of reaction time are pH of 5, H2O2 initial concentration of 3 mmol/L, and catalyst dosage of 2 g/L 2.2.6 Phytotoxicological studies

Ngày tải lên: 13/01/2022, 00:00

... 9Table 4 Training quality of neural network QSPR ANN I(9)-HL(12)-O(1) As observation of eq 13-15 and table 4, the neural model QSPRANN based on the architecture of neural network I(9)-HL(12)-O(1) ... also developed with the neural network technique on the Visual Gene Developer system [46] upon 9 variables of model QSPROLS The architecture of the neural network consist of three layers I(9)-HL(12)-O(1) ... Architecture of neural network I(9)-HL(12)-O(1) The error back-propagation algorithm is used to train the network The hyperbolic tangent transfer function sets on each node of the layer neural network;

Ngày tải lên: 25/10/2022, 13:17

... development of the 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 ... structures of Kohonen neural network K-medians clustering is a variation of K-means, how-ever mathematically medians are calculated instead of means, [13] The selection of standard Kohonen neural network ... field of remote sensing The most commonly used of the classical approach is K-means clustering algorithm [3] while Kohonen network is the most commonly used one of the artificial neural network

Ngày tải lên: 02/11/2022, 11:36

... computation model Artificial Neural Network has been found to be very effective in prediction problems and useful in the development of models[11] Artificial Neural Network (ANN) is one of the artificial ... Karagöz, The use of artificial neural network for prediction of dissolution kinetics, Sci World J 2014 (2014) 1–9 [13] D Deligiorgi, K Philippopoulos, G Kouroupetroglou, Artificial neural network based ... optimal artificial neural network, Int Commun Heat Mass Transfer 76 (2016) 209–214 [18] K Philippopoulos, D Deligiorgi, Application of artificial neural networks for the spatial estimation of wind

Ngày tải lên: 19/11/2022, 11:43

... plasticity, artificial neural networks, spiking neural networks Introduction For a few last years the interest to spiking neural networks has been growing greatly as the result of appearance of neuromorphic ... tasks on autonomous devices, a problem of spiking neural network learning becomes particularly relevant The task of predicting gender of a text author on base of linguistic parameters, that could ... to 1 1.3.1 Results The classification error of ReLU neural network was 0.22 on the testing set Mean classification error on test set of spiking neural network with different Θ and νmax without normalization

Ngày tải lên: 04/12/2022, 16:01

... NETWORK IN DIAGNOSIS oF POWER SYSTEM FAULTS Kesab Bhatta vất Uh i i II ait lỆ *§S§KNO10 3 @-: CRC Lái Trang 2CD Application of Signal Processing Tools and Artificial Neural Network ... information of the type of fault is needed for fault location estimation Because of these requirements, a significant amount of research work has been directed to address the problem of an accurate ... proposed method in this article effect of noise, and is independent of the choice of mother wavelet However, the issues of fault classification and estimation of fault location are not included in

Ngày tải lên: 29/12/2022, 10:40

... Journal of Advanced Manufacturing Technology 22 (2003) [10] J Kusiak, R Kuziak, Modelling of microstructure and mechanical properties of steel using the artificial neural network, Journal of Materials ... austempered ductile iron assisted by artificial neural network, Materials Science (Medžiagotyra) 12 (2006), pp 11-15 [13] A Abdelhay, Application of artificial neural networks to predict the carbon ... a set of perceptrons, being the perceptron a model of a nervous cell (neuron) Such element is the most basic one that we can find on an ANN [16] Perceptron networks are neural networks of a unique

Ngày tải lên: 05/01/2023, 15:21

... instructions for the entire learning process of the neural network. In diagnosing medical pathology, medical professionals often perform an initialestimate of skin melanoma before looking in more ... in the MFSNET model, passing a series of short-circuit neural network modules Each of these modules consists of many short -layer layers with the function of analyzing and extracting hidden characteristics ... softmax, softmax outputs = F.softmax(outputs, dim=1) detach (), the softmax function is applied on outputs with a dimension length of 1 (dim=1), which means it will calculate the probability of

Ngày tải lên: 02/10/2024, 02:37

... content, prediction of noise emission in the machining of wood materials by means of an artificial neural network, optimum CNC cutting condition, reliability of phytosanitary treatment of wood [11–15] ... each subset of data by means of a randomized approach The NeuralWorks Predict Software (NeuralWare Inc., v.3.24.1, Carnegie, PA, USA) was employed to develop de ANN models This software uses ... structure of ANN models and the performance criteria during the development and validation phase Model Output Number of Neurons in the Layers of ANN Models Coefficient of Correlation (R) Coefficient of

Ngày tải lên: 05/11/2025, 23:08

... 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 ... phi tuy n Trong ph n m m NeuroSolution phiên b n 5.0 có s n khá nhi u hàm truy n tuy n tính nh SoftMax Axon, Bias Axon, Axon, Liner Axon và các hàm truy n phi tuy n nh TanhAxon, Sigmoid Axon,

Ngày tải lên: 24/11/2014, 01:42

... Appendix 6 Neural Network Results of Hong Fok Corporation 102 Appendix 7 Neural Network Results of Keppel Land 103 Appendix 8 Neural Network Results of Marco Polo DEV 104 Appendix 9 Neural Network ... Results of Bukit Semawang EST 98 Appendix 3 Neural Network Results of Chemical INDL (FE) 99 Appendix 4 Neural Network Results of City Development 100 Appendix 5 Neural Network Results of Capitaland ... Networks 66 4.3.1 Architecture of BP Neural Networks in Forecasting 66 4.3.2 The Model of OSL Neural Networks and Logit Neural Networks 68 4.4.3 The Monte Carlo Neural Networks 70 4.5 Summary 70

Ngày tải lên: 26/11/2015, 22:57

... with the line of reasoning followed by the model (Asar and McDonald 1994) Trang 213 Neural networks in load forecastingNeural networks, or artificial neural networks (ANN) as they are often called, ... network (MLP) Description of the network Multi-Layer Perceptron network is the most popular neural network type and most ofthe reported neural network short-term load forecasting models are based on ... Classifications of methods 15 Some of the most popular methods 16 Time-of-day models 16 Regression models 17 Stochastic time series models 17 State-space models 19 Expert systems 20 3 NEURAL

Ngày tải lên: 21/10/2016, 09:21

... obtained are results of the neural network Figure 1 Function of a node in neural network nj w  : 1 x 2 x n x j y 1j w w 2 j j q j u j f (u j ) Figure 1 Function of a node in neural network ANN has ... layer, values obtained are results of the neural network Ha, L.H / Journal of Science and Technology in Civil Engineering Artificial Neural Network (ANN) is an Artificial Intelligence technique ... impacts to the project’s profit for new projects The following sections will explain the research approach in detail 2 Artificial Neural Network Artificial Neural Network (ANN) is an information

Ngày tải lên: 11/02/2020, 12:51

... machining of D2 steel with 95% confidence intervals Pal and Chakraborty (2005) developed a back propagation neural network model for the prediction of surface roughness in turning operation of mild ... analysis Davim et al (2008) developed surface roughness prediction models using artificial neural network (ANN) during turning of free machining steel and reported that the cutting speed and feed ... the Order of the Data (response is Ra) Fig 5 Residuals vs fitted value for Ra Fig 6 Residuals vs order of the data for Ra Another predictive model based on ANN (Artificial neural network) is

Ngày tải lên: 14/05/2020, 22:03

... domestic product (GDP) of Saudi Arabia was SAR 2423.40B and its GDP per capita was SAR 204.08K 2 Methods and Materials 2.1 Artificial Neural Network Artificial Neural Network (ANN) is a well-organized ... Kosko A hybrid of Binary Associative Memory and Fuzzy Logic ANN 2.1.1 Basic Model of Artificial Neural Network An ANN mode can be expressed in Fig 1 as follows, x 2 Fig 1 Neural Network Any ... were gradually increasing     Fig 4 The results of Export using Neural Network Fig 5 The results of of Export using ARIMA (1, 1, 2) Fig 6 Plot of ACF of Exports Fig 6 shows that the autocorrelations

Ngày tải lên: 26/05/2020, 22:37

... made in the development of these models Different kinds of models have been implemented for gasification systems, including equilibrium, kinetic and artificial neural networks According to Villanueva ... networks topology An artificial neural network is a system based on the operation of biological neural networks, a computational model inspired Fig e Relative impact (%) of input variables on ... Interpreting neural- network connection weights AI Expert 1991;6:47e51 [19] Khataee AR, Mirzajani O UV/peroxydisulfate oxidation of C I Basic Blue 3: modeling of key factors by artificial neural network Desalination...

Ngày tải lên: 02/08/2016, 09:34

... potential methods One of these novel intelligent theories includes well-known artificial neural network There are many successful commercial and industrial applications using neural network based controlling ... will take the advantage of simplicity of PID control and the neural network s powerful capability of learning, adaptability and tackling nonlinearity And the input signal of the sigmoid function ... initial values of Kp, Ki and Kd are set to be the same of the control parameters of PID controller The purpose of this experiment is to show the effectiveness of the adaptability of control parameter...

Ngày tải lên: 22/07/2014, 02:20

... review of the different artificial intelligence techniques viz., Artificial Neural Networks, Particle Swarm Optimization Algorithm and Genetic Algorithms 2.1 Artificial Neural Networks Artificial neural ... e(i) Error Term in the Neural Network d(i) Desired Output of the Neural Network y(i) Actual Output of the Neural Network PWM Pulse Width Modulation xvii Chapter Introduction Artificial intelligent ... single output of the neuron appears at the axon Artificial neural networks are made up of individual models of the biological neuron connected together to form a network These neuron models are...

Ngày tải lên: 05/10/2015, 22:04

... number of epochs along with percentage efficiency of classification of various faults using ANN are computed A total The architecture of the artificial neural network is as follows: Network type No of ... such results is called neural computing or artificial neural networks ANN mimics biological neurons by simulating some of the workings of the human brain An ANN is made up of processing elements ... that when a new set of features (that is data points with unknown class values) arrive for Table Network statistics of artificial neural network for dry-No Load condition No of neurons in hidden...

Ngày tải lên: 04/04/2016, 22:35