scholarly journals Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

2020 ◽  
Author(s):  
Yanping Zhang ◽  
Wanwei Huang

Abstract With the popularization of computers and various mobile intelligent terminals, intelligent teaching systems based on learners are becoming more and more popular among learners. The above phenomenon has greatly affected and changed the current teaching quality diagnosis methods and models. However, the author found through investigation that the current intelligent teaching quality diagnosis still has different degrees of deficiencies in the design and implementation. In response to the above problems, this paper proposes a teaching quality intelligent diagnosis model based on the combination of wireless sensor networks and fuzzy comprehensive evaluation algorithms. First of all, this article is based on the wireless sensor network to link various levels of intelligent teaching systems, and constructs the information transmission structure of the teaching intelligent diagnosis system. Secondly, this article uses fuzzy comprehensive evaluation and convolutional neural network algorithms to evaluate and excavate intelligent teaching information. Finally, the model successfully passed the simulation test and simulation application, which can provide intelligent diagnosis of teaching quality for modern intelligent teaching system.

Author(s):  
Yanping Zhang ◽  
Wanwei Huang

AbstractWith the popularization of computers and various mobile intelligent terminals, intelligent teaching systems based on learners are becoming more and more popular among learners. The above phenomenon has greatly affected and changed the current teaching quality diagnosis methods and models. However, the author found through investigation that the current intelligent teaching quality diagnosis still has different degrees of deficiencies in the design and implementation. In response to the above problems, this paper proposes a teaching quality intelligent diagnosis model based on the combination of wireless sensor networks and fuzzy comprehensive evaluation algorithms. First of all, this article is based on the wireless sensor network to link various levels of intelligent teaching systems, and constructs the information transmission structure of the teaching intelligent diagnosis system. Secondly, this article uses fuzzy comprehensive evaluation and convolutional neural network algorithms to evaluate and excavate intelligent teaching information. Finally, the model successfully passed the simulation test and simulation application, which can provide intelligent diagnosis of teaching quality for modern intelligent teaching system.


2017 ◽  
Vol 13 (12) ◽  
pp. 85 ◽  
Author(s):  
Ying Xiang ◽  
Miaochao Chen ◽  
Xiaohong Zhuang ◽  
Xiaoxing Li

<p style="margin: 1em 0px;"><span lang="EN-GB"><span style="font-family: Times New Roman; font-size: medium;">In order to reduce the energy consumption and enhance the robustness of wireless sensor network (WSN), this paper proposes a hierarchical clustering routing algorithm based on fuzzy mathematics (HCRAFM). To make a comprehensive analysis of WSN, it is also necessary to detect the robustness of the network. Facing the multiple random variables, the traditional robustness detection models assume that all nodes have the same weight, making it impossible to quantify the analysis indices or obtain accurate results. Thus, the fuzzy mathematics theory was introduced to the WSN robustness detection, forming a fuzzy comprehensive evaluation method. The simulation results show that the HCRAFM strikes a load balance between WSN nodes, extends the life cycle of each node, and prolongs the service life of the network. In addition, the proposed algorithm is proved to have sound robustness and strong applicability.</span></span></p>


2017 ◽  
Vol 13 (03) ◽  
pp. 136
Author(s):  
Xinchun Wang ◽  
Haishan Zhang ◽  
Mi Li ◽  
Ying Li

<span style="font-family: 'Times New Roman',serif; font-size: 12pt; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;">Inherently dynamic in nature, wireless sensor network transmits data less efficient and reliable, and thus the conventional routing protocol is inapplicable to the new type of wireless sensor network. Such being the case, this paper first analyzes this problem and proposes a routing interference optimization mechanism FCE based on distributed fuzzy comprehensive evaluation. The fuzzy principle is introduced to the priority calculation of the node. In doing so, the fuzzy linear transformation principle and the maximum membership principle are used to classify the dynamic nature of candidate nodes and to select well-performed candidates from the optimal candidate nodes. In spite of the few number of those candidates, they are qualified to compete for the right of next-hop forwarding, such that the routing interference will become less probable and the data forwarding is rendered more efficient. Finally, through a simulation test, our method is verified effective.</span>


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