Hybrid Particle Swarm Optimization of Microwave esterification reaction model
Abstract: PSO is an efficient search algorithm,it has been widely used In function optimization, neural network training, pattern classification, fuzzy system control and other fields. Standard PSO algorithm is easy to make the model into a local minimum. Chaotic particle swarm optimization (CPSO), the global extreme adaptive chaos optimization strategy, when there is premature convergence, the optimum particle on the part of the chaos optimization strategy used, out of a local minimum, obtain the global optimum. Chaotic particle swarm optimization using partial least squares support vector machine model. This article papers for the esterification process of microwave showed a strong non-linear as well as numerous factors,Using partial least squares support vector machine based on experimental data on the Microwave Synthesis of Ethyl Salicylate reaction modeling。Model fitting error square is 0.066%, the optimal conditions: acid alcohol ratio of 0.14,the power of 402W, catalyst of 3.00 mL and reaction time of 42 min. The corresponding yield is 80.11%.
Keywords:Esterification; modeling; support vector machine; hybrid particle swarm