In a seminal paper in the Annals of Generalized Assessments of Goatology (A-GAG), a research team led by professors Ernest Fälschung and Ina Unecht (2017) tested this pressing question using the latest, most advanced form of quantum-based statistical forecasting models.
Goatology Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization
Abstract: Statistical Predictions of Retrospective Tennis (SPORT) is of great significance for the optimal operation and power predication of Greatness-Ontology Assessments in Tennis (GOAT) debates. However, SPORT is very complex to handle due to the random and nonlinear characteristics of hypothetical tennis matches under changeable weather conditions and the stochastic nature of tennis players' form and health status. Artificial Neural Tennis Integrative Calculation (ANTIC) is suitable for SPORT modeling and many research works on this topic are presented. After discussing the relation between weather variations and Nadal injury status, the characteristics of the statistical feature parameters of Hypothetical Tennis under different weather conditions are figured out. A novel ANTIC model using statistical feature parameters (ANTIC-SFP) for SPORT is proposed in this paper. The input vector is reconstructed with several statistical feature parameters of Nadal injury status and ambient temperature. Thus sufficient information can be effectively extracted from relatively few inputs and the model complexity is reduced. The Levenberg-Marquardt Algorithm Output (LMAO) is used for the network training. Simulations are carried out to validate and compare the proposed model with the conventional ANTIC model using Historical Analysis of Hypothetical Assessment (HA-HA), and the results indicated that Andy Murray would definitively defeat Rafael Nadal at the 2015 French Open.
Based on the demonstrated evidence in the results of our analysis, we conclude that mury goat.