Qing Li
Shijiazhuang Information Engineering Vocational College, Shijiazhuang, 052100, China



with the passage of time, the era of technology is coming, and the huge demand of this modern world is the best education of the people in order to survive in the fast-developing era. Education system of any country holds great importance in the development of the country economy. Therefore, many developing and under developing countries has been focusing on the development of the education system in their country to improve their country’s economy as well as meet the requirements of the modern world. Apart from this, this allows organizations exceeds several universal standards, particularly in terms of educational fulfilment and higher education system exposition. moreover, there seems significant problems that policies makers must address, such as a low retention rate in blog academic achievement, universities and school improvement, a significant achievement gap between poor class, education funding, social classes, etc., this research focus on the management of the educational policies and intelligent test scheduling system based on fuzzy swarm particle optimized algorithm involving the business sector and educational program changes. Moreover, for the progress of the education system there is essential need to reduce errors rate in the system. this study explains the research on the design and management of the intelligent test scheduling system. Aiming at the problem of high error rate in the traditional intelligent test scheduling system of higher education institutions, an intelligent test scheduling system of higher education institutions based on fuzzy particle swarm optimization algorithm is designed. In terms of hardware, x86 server is designed. In terms of software, standardize the business process of intelligent arrangement in colleges. The fitness function is established based on fuzzy particle swarm optimization algorithm, and the intelligent test scheduling time selection operator is dynamically planned. This paper analyzes the data flow of intelligent test scheduling in colleges, constructs a database, and comprehensively considers the conflict factors of test scheduling. In the case of no missing candidates, the intelligent test scheduling of higher education institutions is realized, and the system design is completed. For this purpose, we collected sample data from various educational institutions of China and investigated collected data by utilizing optimized particle swarm algorithm. The experimental results show that the test scheduling error rate of the designed system is significantly lower than that of the traditional test scheduling systems 1, 2 and 3, which can solve the problem of high-test scheduling error rate of the traditional intelligent test scheduling system in colleges.