Application of Rough Ant Colony Algorithm in Adolescent Psychology

Tao, Cong; Jiang, Lin; Sun, Qihang; Li, Yang

doi:10.1155/2021/6636150

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…It has the ability of video analysis and processing, which can not only detect and identify the types of abnormal objects but also analyze and predict human activities and automatically prompt and alarm according to the harmfulness of the behavior of moving objects [13]. Cong and others believe that it has an advanced network transmission system composed of Internet, intranet, and LAN; using geographic information and 3D modeling technology to provide visual graphical operation interface; the airborne aerial camera can aim from the cloud at the ground monitoring target without regular manual manipulation, so as to realize the long-term monitoring of important targets [14].…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Image Energy Saving Recognition Technology of Monitoring System Based on Ant Colony Algorithm

Bao

2022

Wireless Communications and Mobile Computing

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In order to solve the shortcomings of traditional monitoring and alarm system, the key technology of intelligent video monitoring system-image processing and recognition technology is studied. The image energy-saving recognition technology of monitoring system based on ant colony algorithm is proposed. The ant colony algorithm is used to segment the image, extract the suspicious area, and then deal with the suspicious area separately by using the reasoning based on default rules in artificial intelligence. Using the trained neural network, the recognition experiment is carried out on 40 samples, and the recognition accuracy is more than 93%, which shows that it is very effective to use 7 invariant moments in the target image area as the characteristic parameters of target recognition. The microcomputer 2 renewal for a single target area is identified by using a moment invariant calculation force method and neural network. The execution time of the test on the microcomputer of Saijie 1.0 is microsecond. The experiment proves that it is practical and reliable, meets the real-time requirements, and can transmit the alarm signal and suspicious area image to the alarm center through the network.

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Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Image Energy Saving Recognition Technology of Monitoring System Based on Ant Colony Algorithm

Bao

2022

Wireless Communications and Mobile Computing

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“…He et al (2021) proposed a deep learning‐based psychological education strategy to improve the efficiency of psychological and ideological education. Tao Cong and Qihang Sun (2021) proposed a model for predicting young people's propensity to commit crimes by using an ant colony algorithm; and Shen and Fan (2022) combined a gate‐loop unit (GRU) with an attention mechanism to analyze emotions in ideological and political education and find hidden abnormal psychology.…”

Section: Related Workmentioning

confidence: 99%

Exploration of college students' psychological problems based on online education under COVID‐19

Cai

Wang

Zou

2023

Psychology in the Schools

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As a result of the COVID‐19 pandemic, many college students have been isolated at home and unable to walk into class as usual. This series of protective measures to avoid the spread of the disease may have an additional psychological impact on the lives of college students. The purpose of this study was to propose a strategy for using an intelligent online learning system based on content recommendations and electronic questionnaires in the educational domain. We invited 3000 isolated university students (47.6% male and 52.4% female) to an online trial. It proved to be effective in helping us intervene in students' psychological problems quickly, objectively, efficiently, and in real‐time. In addition, our analysis of the data collected from the intelligent online learning system showed that the degree to which college students' psychological problems were affected by isolation was closely related to students' grade level, family background, major category, and computer proficiency. The current study suggests that the mental health of college students should be well monitored during segregation. Targeted psychological counseling is more necessary for students in upper grades, low‐income families, liberal arts majors, and those with weak computer proficiency to reduce the emotional impact of segregation on students.

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“…There is an increasing interest in applying artificial intelligence technology to the field of mental health education for college students. He [46] proposed a deep learning-based psychological education strategy to improve the efficiency of psychological and ideological education; Tao [47] proposed a model for predicting young people's propensity to commit crimes by using an ant colony algorithm; and Shen [48] combined a gate-loop unit (GRU) with an attention mechanism to analyze emotions in ideological and political education and find hidden abnormal psychology. This artificial intelligence-based emotion analysis can be used in the field of mental health education to identify problems.…”

Section: Combination Of Traditional Questionnaires and Ai Intelligencementioning

confidence: 99%

Psychological Research of College Students Based on Online Education under COVID-19

Wang

Zou

2023

Sustainability

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As a socially sensitive group, college students have a higher risk of mental health problems. However, because of the COVID-19 pandemic, many nonlocal college students were isolated locally and were not able to attend classes as usual. This series of protective measures to avoid the spread of the disease may bring an additional mental impact on college students’ lives. As an important aspect of the sustainable development goals of quality education, education plays a central role in shaping personal and social change towards sustainability. The COVID-19 environment poses a great challenge to the education of university students. The purpose of this study is to propose a strategy to use an intelligent online learning system based on content recommendation and electronic questionnaires in the field of education. We invited 3000 isolated college students (47.6% male and 52.4% female) to participate in an internet trial. It proved to be effective in helping us intervene quickly, objectively, effectively, and in real-time in students’ psychological problems. In addition, according to the data analysis collected by the intelligent online learning system, we found that the degree of isolation regarding college students’ psychological problems was closely related to their grade, family background, professional category, and computer proficiency. This study shows that, during the period of isolation, the mental health of college students should be well monitored. Targeted psychosocial guidance is more needed for students with higher grades, those with low-income families, liberal arts majors, and those with weak computer skills in order to reduce the emotional impact of isolation on students.

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Application of Rough Ant Colony Algorithm in Adolescent Psychology

Cited by 4 publications

References 20 publications

Image Energy Saving Recognition Technology of Monitoring System Based on Ant Colony Algorithm

Image Energy Saving Recognition Technology of Monitoring System Based on Ant Colony Algorithm

Exploration of college students' psychological problems based on online education under COVID‐19

Psychological Research of College Students Based on Online Education under COVID-19

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