A Novel Online Education Reform Model Based on Risky Decision-Making under the Situation of Internet Plus

In the new situation of Internet plus, information technology has been widely applied in education, and hence online education has attracted wide attention from all walks of life. Today’s society is a risk society, and risk is everywhere. Online education reform is also risky, which is determined by many reasons. Some risks will cause certain losses to the online education reform, so based on risky decision-making, it is necessary to carry out online education reform under the new situation of Internet plus. At first, the risky decision-making in online education reform is analyzed, which is the risk of online education reform in risk society and the allocation logic of online education reform. Then, taking interval type-2 fuzzy logic (IT2FL) as the information environment, this study proposes the optimal risky decision-making method based on IT2FL utility functions, IT2FL entropy, and risk preference factor of online education reform to solve the multipath risky decision-making problem of online education reform. Finally, the experimental results show that, in the risky decision-making model, the decision-maker’s risk preference has an impact on the path weight and the ranking of the scheme, and the idea has a certain reference role for risky decision-making. Compared with the three benchmarks, the proposed method has the fewest ranking time with the same ranking results.

An Interval Type-2 Adaptive Neuro-Fuzzy Inference System Based, Artificial Pacemaker Design and Stability Analysis

This paper presents design and simulation of an Interval type-2 fuzzy system (IT2FS) based, Adaptive neuro-fuzzy inference system(ANFIS) pacemaker controller in MATLAB. After designing the type-1 fuzzy logic model, the stability of the designed system has been verified in the time-domain (unit step response). In previous works, type-1 (IT1FS) model step response was analyzed and compared with the other PID and Fuzzy models that only least-square-estimation and the backpropagation algorithms are used for tuning membership functions and generation of type-1 fis (fuzzy inference system) file, but at current work Fuzzy C Means (FCM) method that shows better results has been used. The pacemaker controller determines the pacing rate and adjusts the heart rate of the patient with respect to the reference input signal. The rise-time, overshoot and settling-time have been improved significantly.

Intelligent Contact Force Regulation of Pantograph–Catenary Based on Novel Type-Reduction Technology

In this paper, an intelligent control scheme is proposed to suppress vibrations between the pantograph and the catenary by regulating the contact force to a reference value, thereby achieving stable current collection. In order to reduce the computational cost, an interval Type-2 adaptive fuzzy logic control with the Moradi–Zirhohi–Lin type reduction method is applied to deal with model uncertainties and exterior interference. Based on a simplified pantograph–catenary system model, the comparative simulation results show that variation of the contact force can be attenuated and variation disturbances can be repressed simultaneously. Furthermore, in terms of computational burden, the proposed type reduction method outperforms other type reduction methods.

Fuzzy Multi-objective Linear Programming Problem using DM's Perspective

In this paper, a two-stage method has been proposed for solving Fuzzy Multi-objective Linear Programming Problem (FMOLPP) with Interval Type-2 Triangular Fuzzy Numbers (IT2TFNs) as its coefficients. In the first stage of problem solving, the imprecise nature of the problem has been handled. All technological coefficients given by IT2TFNs are first converted to a closed interval and then the objectives are made crisp by reducing a closed interval into a crisp number and constraints are made crisp by using the concept of acceptability index. The amount by which a specific constraint can be relaxed is decided by the decision maker and thus the problem reduces to a crisp multi-objective linear programming problem (MOLPP). In the second stage of problem solving, the multi-objective nature of the problem is handled by using fuzzy mathematical programming approach. In order to explain the methodology, two numerical examples of the proposed methodology in Production planning and Diet planning problems have also been worked out in this paper.