Apriori Algorithm for the Data Mining of Global Cyberspace Security Issues for Human Participatory Based on Association Rules

Li, Zhi; Li, Xuyu; Tang, Runhua; Zhang, Lin

doi:10.3389/fpsyg.2020.582480

Cited by 37 publications

(26 citation statements)

References 39 publications

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“…The feature of this function is that it can complete any form of nonlinear mapping between the input layer and the output layer. Therefore, it endows the BPNN with absolute advantages in solving the problems of data classification, pattern recognition, and risk assessment [ 7 – 9 ].…”

Section: Bpnn and Evaluation Model Of Asset Qualitymentioning

confidence: 99%

The Application of Artificial Intelligence Technology in the Asset Management of Start-Ups in the Context of Deep Learning

2022

Computational Intelligence and Neuroscience

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With the coninuous improvement and development of artificial intelligence (AI) technology, this technology has been used in the asset management of companies. To improve the asset management level of Chinese start-ups, firstly, back-propagation neural network (BPNN) has been studied in depth, and an evaluation system of the company’s asset quality has been established. Secondly, the BPNN is integrated with the evaluation indicators of asset quality, and an evaluation model of asset quality based on BPNN is constructed. Next, start-up A is taken as the experimental object; the evaluation score of the asset quality of A company is input into the model, which proves that there is still a certain gap between the asset management level of start-ups and mature companies. Finally, to find out the problems of the company’s asset quality, the traditional financial analysis method is used to carry out a specific microanalysis of the evaluation indicators of its asset quality. In view of the existing problems, suggestions are put forward for prudent investment, improve inventory operation efficiency, increase investment in R&D and innovation, improve the quality of sales outlets, and increase the proportion of high-quality intangible assets. The asset quality evaluation system for start-ups established here includes 19 evaluation indicators. The BPNN-based asset quality evaluation model selects 5 mature companies in the same industry as sample companies. The scores of the evaluation indicators of asset quality of the 5 sample companies in the past three years are normalized and input into the model. The model contains 19 nodes of the input layer, 39 nodes of the hidden layer, and 1 node of the output layer. The target error rate is 0.001, the learning rate is 0.1, the number of training times is 1000, and the training function is the trainlm function. This research has a certain reference for the application of AI technology in the asset management of start-ups.

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Section: Bpnn and Evaluation Model Of Asset Qualitymentioning

confidence: 99%

The Application of Artificial Intelligence Technology in the Asset Management of Start-Ups in the Context of Deep Learning

2022

Computational Intelligence and Neuroscience

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“…They demonstrated that these four algorithms can effectively aid in the prevention of terrorist acts. Li, Li, Tang, and Zhang [8] used the Apriori algorithm to compare the frequency of phrases from global professional target websites to explore global cyber space security vulnerabilities. They demonstrated how the Apriori algorithm may be used to research and solve security issues in the global cyber domain.…”

Section: Related Workmentioning

confidence: 99%

A Forensic Investigation of Terrorism in Nigeria: An Apriori Algorithm Approach

Iorliam¹,

Dugeri²,

Akumba³

et al. 2021

JIS

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Investigations towards studying terrorist activities have recently attracted a great amount of research interest. In this paper, we investigate the use of the Apriori algorithm on the Global Terrorism Database (GTD) for forensic investigation purposes. Recently, the Apriori algorithm, which could be considered a forensic tool, has been used to study terrorist activities and patterns across the world. As such, our motivation is to utilise the Apriori algorithm approach on the GTD to study terrorist activities and the areas/states in Nigeria with high frequencies of terrorist activities. We observe that the most preferred method of terrorist attacks in Nigeria is through armed assault. Again, our experiment shows that attacks in Nigeria are mostly successful. Also, we observe from our investigations that most terrorists in Nigeria are not suicidal. The main application of this work can be used by forensic experts to assist law enforcement agencies in decision making when handling terrorist attacks in Nigeria.

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“…The theory suggests that, when confronted with the specific social environment surrounding them, employees’ perceptions are triggered from these situational cues ( Zhu et al, 2019 ; Boudrias et al, 2021 ). Studies along this line found that one’s distinct subjective interpretations of various social cues can become a source of individual behaviors ( Brown et al, 2017 ; Zhu et al, 2019 ; Li et al, 2020 ). Meanwhile, according to regulatory focus theory, occupational stress factors can trigger the change of individual regulatory focus from progressive, explorative strategies to traditional, unadventurous strategies ( Brockner and Higgins, 2001 ; Brenninkmeijer and Hekkert-Koning, 2015 ; González-Cruz et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“Lubricant” or “Stumbling Block”?: The Paradoxical Association Between Team Authoritarian Leadership and Creative Deviance

Jing

Zhu

et al. 2022

Front. Psychol.

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Recently, creative deviance has been lauded to be an innovation-enhancing approach with applications in many new and high-tech domains. Previous study on antecedents to creative deviance remains scattered and vague. Our research conceptualizes creative deviance from the perspective of independent innovation and explores its antecedents, mechanisms, as well as conditions. Team authoritarian leadership is conceptualized as a contradictory unity as it mixes advantages and disadvantages. However, it is surprising to find that there are very few researches that have examined its relevant influence mechanisms and boundary conditions for authoritarian leadership. Contributing to an advanced understanding of authoritarian leadership in research and development teams, we investigated whether team authoritarian leadership is positively or negatively related to creative deviance. Drawing on social information processing theory and regulatory focus theory, we supposed that team authoritarian leadership facilitates creative deviance when the degree is low and inhibits it when the degree is high; dual occupational stress and prevention regulatory focus play mediation roles between team authoritarian leadership and creative deviance respectively, both variables play a chain mediation role in that relationship; and the mindfulness characteristic of an individual moderates the inverted-U team authoritarian leadership-creative deviance association, such that this association is weaker with low individual mindfulness. With two-phase questionnaire data collected from 433 members in 82 R&D teams of high-tech enterprises in electronic information technology, new material technology, new medical technology, resource and environment technology and advanced manufacturing technology randomly selected from five provinces in eastern China, these hypotheses are supported empirically. Overall, we find that, our study broadens antecedents and the relevant occurrence mechanisms of creative deviance when studied through a leadership management lens. Moreover, our research enriches the cognate studies on authoritarian leadership by empirically demonstrating that team authoritarian leadership may function as an double-edged sword of creative deviance in the R&D workplace. These above findings offer insightful thoughts to scholars in the field of authoritarian leadership and bring practical suggestions for team superiors who seek to implement best innovation practice.

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Apriori Algorithm for the Data Mining of Global Cyberspace Security Issues for Human Participatory Based on Association Rules

Cited by 37 publications

References 39 publications

The Application of Artificial Intelligence Technology in the Asset Management of Start-Ups in the Context of Deep Learning

The Application of Artificial Intelligence Technology in the Asset Management of Start-Ups in the Context of Deep Learning

A Forensic Investigation of Terrorism in Nigeria: An Apriori Algorithm Approach

“Lubricant” or “Stumbling Block”?: The Paradoxical Association Between Team Authoritarian Leadership and Creative Deviance

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