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After fitting the transmission parameters of the model, we projected the model forward in time, to simulate the potential future trajectories of the epidemic.
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Yet in our model we project revenues of only $2.4 billion for 2002.
To derive the 2010 main field candidate model, we project the behaviour of the parent model between the final two spline knots forward to 2010.0, up to degree and order 13.
In comparison with our analytical model, we project performance and performance-per-watt for Hadoop and Memcached from a measured baseline while changing one microarchitecture variable (e.g., core frequency and Cycles per Instruction (CPI).
Based on our statistical model, we project that the intervention reduced BNP orders by 21%, or 2,454 tests over three quarters.
Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990.
Finally, due to the mechanistic nature of the climate forcing models, we project historical and future nesting trajectories based on available climate data and under different climate change scenarios.
Using a stochastic, patch-based land change model (FUTURES) we projected urbanization in the North Carolina Piedmont according to status quo trends and several conservation-planning strategies, including constraints on the spatial distribution of development, encouraging infill, and increasing development density.
To construct our App-DDoS defense model, we first projected the proposed attribute matrix into a subspace spanned by the initial principal components,, because it was highly sparse matrix.
The result is a set of rules that can be projected onto a map to produce a potential geographic distribution for the species under investigation in this particular study, we projected models trained within Europe based on European occurrences and European environmental data to worldwide coverages for present-day and 4 future-climate coverage sets.
In order to estimate the effect of global climate change on the potential distribution of P. molurus, we projected our model onto the climatic predictions generated by the CCM3 community circulation model [10] representing temperature increases following hypothesized greenhouse gas increases.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com