[PDF] Top 20 Air quality prediction using artificial neural network
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Air quality prediction using artificial neural network
... Air pollution is an important issue nowadays, being a factor which influences both human health and activities. There are many different chemical substances that contribute to it. These chemicals come from a ... See full document
5
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 ...Maquardt ... See full document
10
PREDICTION OF BUS TRAVEL TIME USING ARTIFICIAL NEURAL NETWORK
... Artifical Neural Network Models: (Smith and Demetsky, 1995; Dia, 2001; Chien et ...model using neural network- based technique to predict traffic volumes for intelligent vehicle highway ... See full document
15
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 ...prices using ... See full document
6
National Stock Exchange Stock and Index Price Direction Prediction using Back-propagation Artificial Neural Network
... It is found in many research literature [2]–[10], The most popular architecture applying for financial market is the multilayer feed-forward neural networks. A standard Neural Network has at least ... See full document
6
Daily SO2 Air Pollution Prediction with the use of Artificial Neural Network Models
... nowadays. Air pollution, especially in the health of human beings, which adversely affect the health of the air and it is foreign matter in the air, the amount of density and reach above the ...of ... See full document
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Prediction of Surface Quality Using Artificial Neural Network for the Green Machining of Inconel 718
... Nickel based super-alloys contain additions of chromium, aluminum, titanium, cobalt, molybdenum, and other elements in varying quantities to give higher performance. With a material of such composition, the problem of ... See full document
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Simulation and optimization of artificial neural network based air quality estimator
... An e-nose is Gas Acquisition System that used an array of multiple sensors. The sensors react to gases with a version of resistance [49, 50]. In Figure 2, it is far viable to look a typical reaction of a sensor S1 (Tin ... See full document
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Prediction of Wirelength in Digital Circuits Using Artificial Neural Network
... a neural network based approach to estimate the total wire length of the digital ...layer neural network is used; a neural network quickly learns the behavior of the placement ... See full document
8
Prediction of Related Party Transactions Using Artificial Neural Network
... multi-layer artificial perceptron neural ...the network will have the ability to adapt to the ...of network generalizability, so that the network is experiencing a large increase in ... See full document
7
Self organizing map and least square support vector machine method for river flow modelling
... Artificial Neural Network (ANN) model has become an alternative forecasting technique used to capture the problems that cannot be solved by using the ARIMA model (Dolling & Varas, ...flow ... See full document
45
Comparative Study of Different Techniques for Heart Disease Prediction System
... • Intelligent and Effective Heart Attack Prediction System Using Data Mining and Artificial Neural Network [8].A methodology for the extraction of significant patterns from the heart ... See full document
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The Potential of Artificial Neural Network Technique in Daily and Monthly Ambient Air Temperature Prediction
... Elman neural networks have been developed in this study to predict the daily and monthly mean, minimum and maximum ambient air temperature in Kerman city, ...maximum air temperature ware considered ... See full document
6
A New Approach for Rainfall Prediction using Artificial Neural Network
... i.e., Artificial Neural ...Environmental Prediction (NCEP) and the International Research Institute ...by using double cross-validation and simple-randomization technique on ...the ... See full document
12
Boulder prediction in rock blasting using artificial neural network
... The artificial neural network seems to be a competence measure to predict rock ...validated using a statistical model developed in SPSS which also showed a correlation coefficient around ... See full document
15
Prediction of Compressive Strength of Concrete using Artificial Neural Network
... The network parameters tested in the proposed model included the following: training data = 60%, validation data = 20% and testing data = 20%, the number of hidden layers was 1, 2 and 3, the number of hidden ... See full document
16
Prediction of indoor air exposure from outdoor air quality using an artificial neural network model for inner city commercial buildings
... for air quality monitoring, all located along busy street canyons in Dublin’s city ...developed artificial neural networks (ANN) based models to predict indoor air quality from ... See full document
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Modelling BOD and COD using Artificial Neural Network with Factor Analysis
... water quality parameters BOD and COD are prominent ...an Artificial Neural Network ...the neural networks is their ability to ...By using factor analysis, the analyst can ... See full document
7
Air Temperature Prediction using Artificial Neural Network for Anyigba, North Central Nigeria
... future prediction. Also, Using the Root Mean Square Error (RMSE) as a means of comparison, the result shows that the model predictions are in good agreement with the values having an average Root Mean ... See full document
6
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
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