[PDF] Top 20 Cotton genotypes selection through artificial neural networks.
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Cotton genotypes selection through artificial neural networks.
... validation through FL, SFI, MAT, and MIC had higher percentage of correctness ...evaluated genotypes to prediction, it was noted that the ANNs using FL individually or in conjunction with the other traits ... See full document
9
Inputs Selection for Artificial Neural Networks for Multivariate time Series
... Recurrent Neural Networks", The 3rd ICEMP, 290-293, Faculty of Engineering, Cairo University, Dec ...id Neural Network Architectures: Equilibrium Systems that Pay Attention", In ...(Eds), ... See full document
8
Heuristic modeling of macromolecule release from PLGA microspheres
... as artificial neural networks (ANNs), feature selec- tion, and genetic programming were ...Feature selection provided by fscaret package and sensitivity analysis performed by ANNs reduced the ... See full document
11
Combat aircraft effectiveness prediction by artificial neural networks
... Although the linear regression yields the predicted effectiveness of unforeseen aircraft, some of them exceed one that is the maximum operational effectiveness, and some are negative which are beyond the minimum ... See full document
330
Remotely-sensed TOA interpretation of synthetic UWB based on neural networks
... threshold selection algorithm using Artificial Neural Networks (ANN) is proposed which is based on a joint metric of the skewness and maximum slope after Energy Detection ... See full document
13
Assessment of Spatial Multi-Criteria Decision-Making with Process of the Artificial Neural Networks Method to Site Selection of the Wastewater Treatment Plant (Case Study: Qeshm Island)
... Site selection the Software Arc gis10, and Ahp combine methods and areas were identified based on the ...of neural network is that the whole data into two groups: training data and test data are ...in ... See full document
6
Colored fiber cotton in the Uberlândia region using artificial neural networks for yield assessment
... In the 2016/2017 season, the yield decrease was strongly influenced by the high incidence of the cotton boll weevil (Anthonomus grandis), the main pest of the crop. The season precipitation displayed a 20% lower ... See full document
13
Forecasting of rainfall using different input selection methods on climate signals for neural network inputs
... and artificial neural networks is ...self-organized neural network (SOM) along with the application of winGamma software were comparatively used as input selection methods to choose the ... See full document
18
Network Data Classification through Artificial Neural Networks and GenClust++ Algorithm
... The prediction accuracy may be altered by the presence of irrelevant or redundant attributes. We will perform two types of feature selection in order to improve the classification accuracy and the total ... See full document
8
Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks
... and artificial intelli- gence ...feature selection and a clas- sifier based on a general regression neural network (GRNN) and multilayer perceptron (MLP) to classify ... See full document
11
Selection index as a priori information for using artificial neural networks to classify alfalfa genotypes
... Simultaneous selection has been the most widely used strategy in alfalfa breeding (Basigalup and Odorizzi, ...published selection indexes, the one proposed by Taí (1977) is applicable to selection of ... See full document
11
Feature selection of microarray data using genetic algorithms and artificial neural networks
... Machine learning methods require the specification of several parameters by the user. The changing of these values can greatly alter the efficiency and performance of an evolutionary system. Several pre-runs were ... See full document
71
Prediction of Stock Prices Using Artificial N...
... defines artificial neural networks, section III describes the applications of neural networks, section IV shows the characteristics of artificial neural networks, ... See full document
6
Prediction of Compressive Strength of Concrete using Artificial Neural Network
... any. Artificial Neural Network (ANN) is used to predict the compressive strength of ...the networks. Networks are trained and tested at various learning rate and momentum factor and after many ... See full document
16
On the application and design of artificial neural networks for motor fault detection. II.
... P of the use of artificial neural networks in motor fault detection applications. In Part I1 of this paper, we will discuss how to design an artificial neural network for[r] ... See full document
8
Performance Analysis of Combine Harvester using Hybrid Model of Artificial Neural Networks Particle Swarm Optimization
... to artificial neural networks (ANNs) ...single-layer artificial neural network, in improving the performance of a John Deere 1055 Combine ...of neural networks have ... See full document
6
HANDWRITTEN DEVANAGARI CHARACTERS RECOGNITION THROUGH SEGMENTATION AND ARTIFICIAL NEURAL NETWORKS
... Abstract: Handwritten character recognition is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices. ... See full document
7
Artifcial neural network approach for the prediction of terminal falling velocity of non-spherical particles through Newtonian and non-Newtonian fluids
... of Artificial Neural Networks (ANNs) for the prediction of non- spherical particles terminal falling velocity through Newtonian and non- Newtonian (power law) liquids was investigated using ... See full document
14
Predictive Analytics: A Review of Trends and Techniques
... conditioner increases in summers and demand of geysers increases in winter. The customers search for the product depending the season. Here the XYZ Company will collect all the search data of customers that in which ... See full document
7
A Study on Effective Algorithm for Medical Decision Making System
... (NDT), Artificial neural networks could be used in every situation in which exists a relationship between some variables that can be considered inputs and other variables that can be ... See full document
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