Fixed unconsistent use of acronyms

Sections/10_Introduction.tex

@@ -35,7 +35,7 @@ The idea of using Gaussian Processes as regression models for control of dynamic
 systems is not new, and has already been explored a number of times. A general
 description of their use, along with the necessary theory and some example
 implementations is given in~\cite{kocijanModellingControlDynamic2016}.
-In~\cite{pleweSupervisoryModelPredictive2020}, a \acrlong{gp} Model with a
+In~\cite{pleweSupervisoryModelPredictive2020}, a \acrshort{gp} Model with a
 \acrlong{rq} Kernel is used for temperature set point optimization.
 
 Gaussian Processes for building control have also been studied before in the
@@ -66,7 +66,7 @@ the original identified model goes further and further into the extrapolated
 regions.
 
 This project tries to combine the use of online learning control schemes with
-\acrlong{gp} Models through implementing \acrlong{svgp} Models. \acrshort{svgp}s
+\acrshort{gp} Models through implementing \acrfull{svgp} Models. \acrshort{svgp}s
 provide means of extending the use of \acrshort{gp}s to larger datasets, thus
 enabling the periodic re-training of the model to include all the historically
 available data.
@@ -81,7 +81,7 @@ multiple control schemes using both classical \acrshort{gp}s, as well as
 Section~\ref{sec:gaussian_processes} provides the mathematical background for
 understanding \acrshort{gp}s, as well as the definition in very broad strokes of
 \acrshort{svgp}s and their differences from the classical implementation of
-\acrlong{gp}es. This information is later used for comparing their performances
+\acrshort{gp}s. This information is later used for comparing their performances
 and outlining their respective pros and cons.
 
 Section~\ref{sec:CARNOT} goes into the details of the implementation of the