[PDF] Top 20 DATA PREDICTION FROM A SET OF SAMPLED DATA USING ARTIFICIAL NEURAL NETWORK IN MATLAB SIMULINK
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DATA PREDICTION FROM A SET OF SAMPLED DATA USING ARTIFICIAL NEURAL NETWORK IN MATLAB SIMULINK
... and prediction power of the Neural ...function. Neural networks have been successfully used for ...series prediction like Box-Jenkins or ARIMA assumes that there is a linear relationship ... See full document
20
Prediction of Compressive Strength of High Performance Concrete using Artificial Neural Network (ANN) Models
... of using Portland ...developed using Artificial Neural Network (ANN) and Multiple Regression Analysis (MRA for the prediction of compressive strength of concrete with SCMs like ... See full document
10
INVESTIGATING DATA MINING BY ARTIFICIAL NEURAL NETWORK: A CASE OF REAL ESTATE PROPERTY EVALUATION
... analyzing data from different perspectives and summarizing it into useful information that can be used to increase revenue, cut costs, forecasting, decision support ...used MATLAB as a platform to ... See full document
6
Comparative Study of Different Techniques for Heart Disease Prediction System
... forward artificial neural network model that maps sets of input data onto a set of appropriate ...distinguish data that are not linearly ... See full document
10
Prediction of Bio-informatics Data Related to Toxicant (Gallium Arsenide) using Artificial Neural Network
... for neural network based on mathematics and ...combine artificial neurons in order to process ...an artificial neuron the output can be obtained for any specific ...the network ... See full document
6
Exergetic Performance Prediction of a Roughened Solar Air Heater Using Artificial Neural Network
... systems using an ANN model has not been done so ...by using actual experimental data and the calculated values of ...fifty data sets have been obtained by conducting experiments on three ... See full document
12
Rainfall Prediction using Data Mining Techniques
... the neural networks in the extraction of the features of the systems, even in the cases that there is not much information about the system ...perceptron network with back propagation algorithm is used to ... See full document
5
Prediction Modeling and Mapping of Soil Carbon Content Using Artificial Neural Network, Hyperspectral Satellite Data and Field Spectroscopy
... spatial data for use in soil ...derived from remote sensing provide precious in- formation for characterization of ...occurs from the visible to the shortwave infrared—with absorption bands around ... See full document
10
Biomedical Prediction of Radial Size of Powdered Element using Artificial Neural Network
... determined using ANN modeling from different combinations of architectures and transfer functions by means of a feed-forward neural network model which renders the effect of volume of ... See full document
10
Prediction of Drug Lipophilicity Using Back Propagation Artificial Neural Network Modeling
... target data are values of log P o/w ; thus, a supervised learning method should be ...each set of the four input variables, MV, HLB, HB and PSA for any drug ...our network requires four input units ... See full document
10
Machine Learning and Artificial Neural Network Process – Viability and Implications in Stock Market Prediction
... the prediction accuracy and ...In prediction the significant variables are “Low”,”Open” and “High” and the variable ”Month” does not give any support for the ...the prediction through linear ... See full document
6
Prediction of prostate cancer by deep learning with multilayer artificial neural network
... 3). Using the obtained coefficients, the probability of prostate cancer detection, accuracy of prostate cancer prediction, and area under the ROC curve (AUC) were output from test ... See full document
13
Prediction of Stock Prices Using Artificial N...
... presents prediction of stock prices using Artificial Neural Network (“ANN”) approach, its characteristics, classification and uses of Applications are precisely ...of data. ... See full document
6
Backpropagation Neural Network Algorithm for Water Level Prediction
... level prediction information system by applying back propagation neural network algorithm begins with the actual data entry stage of time and water level which is then stored in the ...level ... See full document
7
A GENETIC ALGORITHM OPTIMIZED MULTI-LAYER PERCEPTRON FOR SOFTWARE DEFECT PREDICTION
... algorithm from becoming trapped in local minima as the training of the network ...main data that GAs need is some performance value that decides how great a given set of weights ...gradient ... See full document
10
Study on Experiments of Artificial Neural Network Using Spatial Data
... In our experiments we tested standard ANN-BP composed of seven input layers, one and two hidden layers and four output layers. Some parameters have a relationship based on experiments carried out 20 simulations, so the ... See full document
5
Improved the Prediction of Multiple Linear Regression Model Performance Using the Hybrid Approach: A Case Study of Chlorophyll a at the Offshore Kuala Terengganu, Terengganu
... Thus, Artificial Neural Net- work (ANN) was adopted as an approach to extracting information, required no priori assumptions about the model in terms of mathematical relationships or distribution ... See full document
17
Predicting Pavement Performance Utilizing Artificial Neural Network (ANN)
... Historical data was used on in both ANN and MLR models to predict individual distresses for three pavement types, ACC, PCC, and COM ...obtained from the ANN models were compared with the results from ... See full document
5
The Influence of Composite Laminate Stacking Sequence on Failure Load of Bonding Joints Using Experimental and Artificial Neural Networks Methods
... Failure load prediction of single lap adhesive joints using artificial neural networks. Aydın, An artificial neural network model for predicting compression strength of heat [r] ... See full document
10
Prediction of Rice Diseases Using Convolutional Neural Network (in Rstudio)
... In this paper, particularly focused on identifying the diseases which occur in paddy using r language .By improving the training images we achieve better results. In future, we can also predict disease name and ... See full document
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