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Assessment of the Contribution of Information Adversarial Technology to Educational Development in the Context of Neural Networks

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  • YiLin Shao
  • HanNing Lu
  • QingYuan Liu
  • GaoShuo Li
  • Ning Cao

Abstract

Since the 3rd technological revolution, electronic information has developed at an increasingly rapid pace and has been widely used in various aspects of people’s lives and social production. With the advent of the information society, information security is particularly important and is related to the security of various industries and fields, such as transportation, national defense, and economy. If there is a problem in information, it means that there is a problem in information countermeasures, which leads to the emergence of information countermeasures technology. At present, with the accelerated progress of socialization, the requirements for information technology talents have been raised accordingly, so schools are required to pay attention to the education and training of talents in this area to meet the needs of society and speed up the development of society. Moreover, more and more scholars are recognizing the significance of data analysis technology for education development, and some scholars have constructed learning prediction models from different educational environments and perspectives. However, some of the models have their own limitations and thus can hinder the parameter setting. Therefore, educational researchers need to combine the characteristics of their own educational environment to build a widely adaptable predictive model to provide a good foundation for the development of education. Also, on that basis, information confrontation technology should be applied to explore diverse teaching courses, improve the traditional teaching philosophy, improve the management and evaluation mechanism, provide students with diverse learning styles, emphasize the practical nature of learning, and continuously improve students’ independent problem-solving ability.

Suggested Citation

  • YiLin Shao & HanNing Lu & QingYuan Liu & GaoShuo Li & Ning Cao, 2022. "Assessment of the Contribution of Information Adversarial Technology to Educational Development in the Context of Neural Networks," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-7, August.
  • Handle: RePEc:hin:jnlmpe:8258796
    DOI: 10.1155/2022/8258796
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