[PDF] Top 20 Estimating soybean yields with artificial neural networks
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Estimating soybean yields with artificial neural networks
... of artificial neural networks ...estimate soybean productivity based on growth habit, sowing density and agronomic characteristics using an ANN multilayer perceptron ...2013/2014 ... See full document
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Estimating the Number of Test Workers Necessary for a Software Testing Process Using Artificial Neural Networks
... resources. Estimating time, cost, and staff helps sustain the monitoring and controlling of project activities and, in the end, produce ...concerned with providing an estimate of the expected cost, ... See full document
7
Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks
... Artificial neural networks (ANNs), as one of the most attractive branches in artificial intelligence, has the potential to handle problems such as modeling, estimating, prediction, ... See full document
8
RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks.
... gene networks based on an ensemble of multilayer ...network, estimating its neighborhood ...larger networks and on biological data consisting of submodules of Escherichia ...together with two ... See full document
19
Estimating Suspended Sediment by Artificial Neural Network (ANN), Decision Trees (DT) and Sediment Rating Curve (SRC) Models (Case study: Lorestan Province, Iran)
... ANN with back propagation and Levenberg-Maquardt algorithms, radial basis function (RBF), Fuzzy Logic, and decision tree algorithms such as M5 and REP Tree for predicting the suspended sediment concentration at ... See full document
8
Development of a zero trans margarine from soybean-based interesterified fats formulated using artificial neural networks
... Figure 1 shows the consistency values (yield values) for the commercial fats and ANN formulations (commercial fat 1 and ANN formulations (a), commercial fat 2 and ANN formulations (b)). The commercial fat 1 was ... See full document
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Estimating Bankruptcy Using Neural Networks Trained with Hidden Layer Learning Vector Quantization
... that neural network is a complementary tool for the credit risk classification ...of artificial neural networks ...that neural networks have lower generalization capability ... See full document
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Application of Artificial Neural Networks for Predicting Generated Wind Power
... USA ranks first amongst the wind energy generation countries in the world. The wind energy production capacity of India is 102,788 MW at 50 meters above the ground level [1, 7]. India holds the fifth position in the ... See full document
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Artificial neural networks for compression of gray scale images: a benchmark
... begins with the decomposition of the image at different scales using a wavelet transform (WT) in order to obtain an orthogonal wavelet representation of the image, continues with the application for each ... See full document
12
Design of Circular Microstrip Antenna Using Artificial Neural Networks
... an artificial neural network (ANN) model has been developed for design of circular microstrip patch ...proposed neural model completely bypasses the repeated use of complex iterative process for ... See full document
4
ARTIFICIAL NEURAL NETWORKS - AN APPLICATION TO STOCK MARKET VOLATILITY
... White [1988] was the fist to be Neural Networks for stock market fore casting. Ripley [1993] claims that although compressions of ANNs to other methods are rare, however, when done carefully, often show ... See full document
10
Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America
... Abstract. Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variabil- ity and climate change. This paper introduces an application of artificial neural ... See full document
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Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran
... using neural network classification method. Neural networks method is considered as a proper method for classification of land use and land cover, because it can be used for all kinds of data in ... See full document
6
A survey of data mining & its applications
... Learning, Artificial Intelligence, Pattern Recognition and Computation capabilities have evolved the present day’s data mining applications and these applications have enriched the various fields of human life ... See full document
5
Artificial Neural Networks versus Box-Jenkins Methodology in Tourism Demand Analysis
... series, with the aim of “cleaning” this ...domain with the application of one simple and another seasonal ...ANN with the best results in the validation group, for each of the ...session, with ... See full document
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Identification of common city characteristics influencing room occupancy
... Chattopadhyay, M., and Mitra, S.K. (2018), “Determinants of revenue per available room: Influential roles of average daily rate, demand, seasonality and yearly trend”, International Journal of Hospitality Management. ... See full document
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VOICE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS AND GAUSSIAN MIXTURE MODELS
... speakers with each speaker providing specific sets of utterances through a microphone terminal or ...useful with implications on the speech feature classification ...utterances with the respective ... See full document
10
Wavelet transform and artificial neural networks applied to voice disorders
... Abstract—The amount of non-invasive methods of diagnosis has increased due to the need for simple, quick and painless tests. Due to the growth of technology that provides the means for extraction and signal processing, ... See full document
6
Digital soil mapping using reference area and artificial neural networks
... using artificial neural networks (ANN) and environmental variables that express soil- landscape ...studied. With the mapping units identified together with the environmental variables ... See full document
8
Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
... an artificial neural network considering the methodology of Eberhart and ...blocks, with two ...The artificial neural network was able to satisfactorily classify the ...compared ... See full document
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