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The Conductance model was used to predict yields of B. oleracea, S. nigrum and V. persica grown in both monoculture and binary weed-crop mixtures over a range of temporal and spatial scales.
The crop model Biomass Simulation Tool for Agricultural Resources (BioSTAR) [17, 18] has been developed to simulate climate and soil-dependent biomass yields for bioenergy crops, but obviously it can also be used to predict yields for food crops like wheat or rye.
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Finally, in the third part these distributions are used to predict yield stresses.
Crop models are used to predict yield and resource requirements as well as to evaluate different climate or management scenarios at a specific site.
In each partition two models (P, pedigree and PM, pedigree + markers) were fitted and used to predict yield in the TST data set.
The ANN model which was trained and tested against experimental data (see Sects. 3.1, 3.2) was used to predict FAME yields at different input datasets.
The mathematical model can be used to predict product yields, coking buildup inside the tube wall, run length (i.e. the time between two consecutive decoking operations), residence time and pressure drop.
If the reaction can be characterized by a single activation energy, knowledge of the thermal time distribution based on this activation energy can be used to predict the yield of a first order reaction uniquely and to closely bound the yield for reactions of order other than first.
In this paper, experimental values of three variables, mycelial dry weight, and extracellular polysaccharide in Table 2 were normalized in the range of 0 to 1. Then three neurons in the input layer, three in a hidden layer, and one in the output layer using the tanh transfer function were used to predict the yield of mycelial biomass and EPS, respectively (Matlab 7.1 software).
Surface response models are used to predict the yield.
Based upon the experimental data, an ANN model has been developed which is used to predict %FAME yield for a given set of input conditions.
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