The proliferation of Internet information technology has fundamentally changed the way of learning. It is now a research hotspot to improve teaching effect in col-leges with Internet information technology. Starting from the actual needs of col-lege teaching, this paper designs a college teaching system based on various In-ternet information technologies. Specifically, the front end was developed under the lightweight progressive Vue.js framework, which relies on the model–view–view model (MVVM); the overall structure of the system was set up based on the browser-server (B/S) architecture; the system functions were realized through HTML5, Node.js and database technology; the compatibility between mobile terminal and desktop was realized under Bootstrap. The system test shows that the Vue.js-based college teaching system operated stably, achieved the design goals and satisfied user demand. The research findings shed important new light on modernization and quality of college teaching.

Complex system engineering often has high fuzziness and multiple constraints. In this case, it is difficult to achieve consistent results through predictive analysis. To solve the problem, this paper explores the key techniques and methods for predictive analysis on complex systems, and puts forward an improved strategy for multi-constrained fuzzy predictive analysis. The author explained the normalization, weighting, granularity setting and classic domain of the attributes of multiple constraints, introduced the calculation of the fuzzy distance and fuzzy closeness for the attributes of multiple constraints, and detailed the realization of our algorithm and model multi-constrained fuzzy predictive analysis. The effectiveness and feasibility of our algorithm and model were demonstrated through comparison with relevant data in the literature. The results show that the results of our approach agree with those of the literature. The proposed algorithm and model provide a good theoretical basis to predictive analysis of complex system engineering, especially that with multiple fuzzy constraints.

Aiming at problems of solving multiple quadratic equation systems, the redundancy of extending equations by eXtended Linearization (XL) algorithm is analyzed. It is proved that there is redundancy in equations extended by XL algorithm. The upper bound, [mn(n+3) m(m 3)]/2, of the number of linearly independent equations in the new system of equations, which extends from n-variable quadratic equations consisting of m equations, is given.

No abstract

No abstract