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This section reports the results of the genetic framework based on techniques discussed in Section 2.3 and presents the results for each RQ.
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A model effluent treatment scheme based on the various techniques discussed in the present work has been presented.
In this paper, the feasibility of roughness measurements based on interferometric techniques is discussed.
In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE.
Based on the methodology discussed in the previous section the algorithm for proposed multi document summarization using semantic similarity based clustering technique is presented in this section.
Fault diagnosis based on SVM is discussed.
The three kinds of semi-formal techniques discussed are bounded model checking based on SAT solvers, symbolic simulation techniques based on BDDs, and smart simulation techniques that use formal methods to bolster traditional simulation-based validation.
The computational techniques based on cubic spline are discussed in detail by Khan et al. [17] and Kumar et al. [18] for the differential equations.
The data mining techniques discussed in Section "Suggestive analysis" are mostly based on topological information.
were discussed, we concluded that those based on sender receiver techniques combine a reduced synchronization error along with a low implementation complexity and better energy efficiency.
The problem is simulated using a discrete event based simulation program and solved on a more practical scale using the heuristic search techniques discussed in the previous sections.
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