Optimization system of musical expression for the music genre classification

Recently, the introduction of CT (Culture Technology) in the intelligence system was forming a new paradigm. Among these, research on musical fountain is still in the basic research phase has been started. Musical fountain System is required scenario to control the music and nozzle of fountain. In generally, these musical fountain scenarios created by the experts. So musical fountain need too much cost of maintenance for subsidiary facilities. In this paper, using the Beat Tracking Algorithm, optimized musical expression intelligent fountain system is proposed. Also, we proposed new classification of music genre to reduce the maintenance costs of musical fountain. We simply tag the emotional adjectives, as set apart as a genre of music was re-classified. In this paper, the newly defined criteria to classify the genre, SVMs (Support Vector Machines) algorithm, the weights applied by the Gaussian distribution to determine the optimal hyper plane, VCMs (Variance-Considered Machines)algorithm is used. The proposed use of this system to generate a musical fountain scenario can significantly reduce the time required, a in terms of cost can be reduced significantly.