The level classification of agricultural equipment based on support vector machine

In view of the unbalanced development of agricultural equipment in the reclamation farms in Heilongjiang,we use the methods of multi-class support vector machines and principal component analysis to evaluate the differences of agricultural machinery equipment level in these farms.The level of agricultural equipment is divided into three grades.We select ten evaluation indexes from the aspect of the total equipment amount,development speed and volume index.Five major synthetic indicators are identified by using principal component analysis with a new formulation based on the K-SVCR method.We then transform it as a complementarity problem and further a strongly convex unconstrained optimization problem by using the implicit Lagrangian function.Then a fast Newton algorithm with global and finite termination properties is established for solving the resulting optimization problem.For measuring the developmental condition of the agricultural equipment in 98 farms,evaluating and analyzing the comprehensive differences of agricultural equipment level o in each farm,we put forward the policy recommendations to coordinate the development of farm machinery and equipment in each farm in Heilongjiang Reclamation area.