Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

Design and implementation of international agricultural and biological engineering expert management system based on WEB mode

Agriculture and biological engineering are the foundation of agricultural modernization,and related countries have also issued relevant policies to guide the development of agriculture and biotechnology.Agricultural and biological engineering experts are the intellectual resources in the field.At present,there is less research on the management and maintenance of agricultural and biological engineering experts,and there is a lack of software systems in this area.In order to realize the management and maintenance of agricultural and biological engineering expert information,a service platform for the international agricultural and biological engineering expert system based on the B/S framework has been developed.The background of the system used C#as the development language,and the foreground used JavaScript technology and Bootstrap.The software adopted ASP.NET MVC as the web development framework and used the Entity Framework to operate the SQL Server background database.The system has the function of searching and querying agricultural and biological engineering expert information according to keywords,and implements the functions of adding,deleting,and modifying data records,and the function of generating spreadsheets and importing spreadsheet data.The development of this system provides effective management tools for the maintenance and construction of agricultural and biological engineering expert databases and lays a good foundation for the construction of agricultural and biological engineering think tanks.