[PDF] Top 20 Optimization of Medium Components Using Artificial Neural Networks
Has 10000 "Optimization of Medium Components Using Artificial Neural Networks" found on our website. Below are the top 20 most common "Optimization of Medium Components Using Artificial Neural Networks".
Optimization of Medium Components Using Artificial Neural Networks
... the medium can be reduced and condition probably for growth is ...modeling using ANN software, the model generated R2 values of ...density medium was ...model using ANNs ... See full document
9
Prediction & Optimization of End Milling Process Parameters Using Artificial Neural Networks
... design. Artificial Neural networks (ANN) program available in Matlab software is used to establish the relationships between the input process parameters and the output ...through Artificial ... See full document
6
Fast Vibroacoustic Optimization of Mechanical Structures Using Artificial Neural Networks
... acoustic optimization, it is experienced that there is a lack of study on the combination of artificial neural networks as a virtual function approximation tool and simulated annealing method ... See full document
5
Pareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms
... by using two-element wing models with morphing flap; therefore, optimal design points should be identified by utilizing a multi-objective ...multi-objective optimization will be used in the ensuing ... See full document
7
Genetic Optimization of Artificial Neural Networks to Forecast Virioplankton Abundance from Cytometric Data
... tion to the fact that VBR, which contain the prokaryotes as one of its components, can be related statistically to an autocorrelation. Together, these results led us to specu- late at large we are looking to ... See full document
10
Design and Optimization of Microstrip Patch Antenna using Artificial Neural Networks
... the optimization of design parameters is most important consideration in order to obtain efficient computational ...the optimization of design are proposed in literature, which includes genetic algorithm ... See full document
6
Prediction of agricultural tractor noise levels using artificial neural networks
... user. Networks with biases, a sigmoid layer, and a linear output layer are capable of approximating any function with a finite number of ...standard optimization techniques, such as conjugate gradient and ... See full document
7
Experimental Investigation of Classification Algorithms for Predicting Lesion Type on Breast DCE MR Images
... as artificial neural networks, support vector machines and artificial bee colony optimization algorithm trained neural ...selection using the statistical hypothesis t-test ... See full document
8
Soft Computing in Bioinformatics: Methodologies and Applications
... functionally using the major components of soft computing like Fuzzy Sets (FS), Artificial Neural Networks (ANN), Evolutionary Algorithms (EAs) (including genetic algorithms (GAs), ... See full document
7
Shape Optimization of Pedestals Using Artificial Neural Network
... and artificial neural networks in a gradientless method of shape ...shape optimization approach for minimizing stress concentration ...for optimization called as ‘curvature function ... See full document
7
Optimization of surface roughness using RSM and ANN modelling on thin walled machining under biodegradable cutting fluids
... and Artificial Neural Networks (ANN) in prediction and optimization surface roughness milling thin-wall steel using flood coconut ... See full document
11
Title: DIABETES DIAGNOSIS USING MACHINE LEARNING
... Abstract— Artificial neural networks have been in the position of producing complex dynamics in control applications over the last decade, especially when they are linked to ...ANN using ... See full document
6
New Intelligent Classification Techniques for Diagnosis of Diabetes Mellitus based on Modified PSO
... Hybrid optimization techniques are in the form Artificial Neural networks, Genetic Algorithm, Fuzzy classifier, Support Vector Machine, Least Squares Support Vector Machine, Particle Swarm ... See full document
7
Title: CLASSIFICATION ON BREAST CANCER USING GENETIC ALGORITHM TRAINED NEURAL NETWORK
... Abstract— Artificial neural networks have been in the position of producing complex dynamics in control applications over the last decade, especially when they are linked to ...ANN using ... See full document
7
Diagnosis of Breast Cancer by Combining the Techniques of Data Mining and Artificial Immune System
... Currently, using FNA as a method for tumor mass sampling and testing on that type of tumor (benign and malignant) is ...of neural network weights is done using an artificial immunological ... See full document
8
Multi-Physics Parametric Modeling of Microwave Passive Components Using Artificial Neural Networks
... approach using artificial neural networks (ANNs) for microwave passive components is ...passive components with respect to the multi-physics input ...responses using low ... See full document
10
SMOKE DETECTION BASED ON IMAGE PROCESSING BY USING GREY AND TRANSPARENCY FEATURES
... the neural networks is often a more important factor than the number of hidden ...that neural network has a limited capacity to deal with seasonality in time series, its clearly indicate that ... See full document
11
FORECASTING ENERGY DEMAND FOR A HOUSE USING ARTIFICIAL NEURAL NETWORK
... The Neural networks are widely using for short-term, and to a lesser degree medium and long term, demand ...is using both neural network and abductive network for modeling, and ... See full document
6
Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America
... studying artificial neural networks (ANNs) and multiple linear regression (MLR), found that the neural-network method performed better than the linear- regression method, although both showed ... See full document
8
Correlation analysis and prediction of personality traits using graphic data collections
... of neural networks with a small number of convolution layers (from one to two) do not provide sufficient accuracy for identifying personality traits; increasing the size of the input images sequentially ... See full document
7
Related subjects