Computer network security evaluation simulation model based on neural network

Tang, Ying; Elhoseny, Mohamed

doi:10.3233/jifs-179121

Cited by 70 publications

(27 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…VR is considered to be the highest level application of multimedia. It combines computer technology, visual physiology, and visual psychology, simulation technology, sensing technology, speech recognition, artificial intelligence and other high-tech technical means, which is the combination of new high-tech technologies in modern society [21]- [23]. The three-dimensional dynamic world constructed by VR technology has strong fidelity and real-time performance, which has the following characteristics: 1) Conceivability: in the three-dimensional dynamic space, users can obtain any virtual information in the space according to their own perception and judgment.…”

Section: ) Characteristics Of Vr Technologymentioning

confidence: 99%

Retracted: Significance and Possibility of VR Technology Embedded in the Teaching of Ideological and Political Theory Course in Colleges and Universities

Zhang

Chen

Yin³

2020

IEEE Access

View full text Add to dashboard Cite

The main function of Ideological and political theory course in Colleges and universities is to carry out ideological and political education and moral education to help students establish a good world outlook, outlook on life and values. The main purpose of this paper is to combine VR technology with ideological and political theory course in Colleges and universities. The data of this experiment is from our school to select economics class 1, economics class 2, financial management class 1, and financial management class 2. The average score of Ideological and political theory course in the final examination of last semester of the four classes is close to and close to each other, and 50 people are selected as samples. They were randomly divided into two groups: VR teaching group (economics class 1: A1, financial management class 1: B1) and general teaching group (economics class 2: A2, financial management class 2: B2). VR teaching group lasted for one month, VR ideological and political theory class classroom teaching, ordinary teaching group or traditional teaching. One month later, the four groups of students were tested for ideological and political theory. Before and after the experiment, group A1 and group B1 were investigated: the learning attitude and classroom state of Ideological and political theory course. The experimental results show that: after VR classroom learning, the proportion of A1 and B2 groups who like to think about political theory class increased by 8.2% and 8.14%. The proportion of A1 and B1 aversion to ideological and political theory courses decreased to 1.2% and 3.54%. After VR classroom teaching, the average score of Ideological and political theory course in A1 and B1 groups was 13.81 and 9.68 points higher than that of A2 and B2 groups, and the scores were increased by 19.7% and 13.5%. VR classroom teaching can stimulate students' interest in learning; promote the understanding of knowledge, as well as the establishment of emotional attitude and values. INDEX TERMS VR technology, ideological and political theory course, colleges and universities, significance and possibility.

show abstract

Section: ) Characteristics Of Vr Technologymentioning

confidence: 99%

Retracted: Significance and Possibility of VR Technology Embedded in the Teaching of Ideological and Political Theory Course in Colleges and Universities

Zhang

Chen

Yin³

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In the past, linear time series models such as ARMA and GARCH were often used for forecasting. In recent years, with the development of mechanical learning, various neural networks have begun to be suitable for stock price forecasting [2].…”

Section: Introductionmentioning

confidence: 99%

Retracted: Mathematical Model of Yield Forecast Based on Long and Short-Term Memory Image Neural Network

2024

View full text Add to dashboard Cite

Yield prediction has always been the focus of stock investors' attention in stock investment. This research uses the virtual stock scene constructed by VR technology to explore the mathematical model of return rate prediction. First, neural nodes, activation functions and output functions are designed under the LSTM framework, and a recurrent neural network that can handle long-term sequences is constructed. Use VR technology to simulate stock data and extract key frames from the image sequence. Aiming at the timing of key curve nodes, this study uses a long and short-term memory neural network that is good at processing time series data to classify curve trends, and realizes the identification of abnormal fluctuations in virtual scenes of stock images. Then, according to the existing probability control asset allocation theory, the index of investment allocation is adjusted from the entire time series to a dynamic time series. According to the stock price decomposition of EEMD, the EEMD-LSTM model is constructed to predict the stock market price. Use EEMD to decompose the original sequence to obtain IMF and trend items containing various timescale characteristics. Then, the LSTM neural network is used to predict and analyze each rate of return, and the analysis software Python is used to process and count the predicted results. At the same time, retrospective restrictions are regarded as riskier assets. Finally, the investment is made under conditions that do not allow shorting in the VR simulation scenario. The accuracy of the calculation is more than 70% except for the Shanghai and Shenzhen 300 Index reaching 66%. The research results show that in the case of different stock price forecasts, the prediction ability of LSTM neural network has been greatly improved compared with that of support vector machine, which fully reflects the advantages of LSTM in time series prediction.

show abstract

“…The high cost of this research is not conducive to popularization [ 4 ]. George Jr proposed that backside culling is a preprocessing technology for computer graphics that can speed up the rendering of polyhedrons and showed how to modify this technology to reduce collision detection in physics-based simulation and animation systems [ 5 ]. For necessary boundary element inspection, at each time step, George Jr determines an a priori surface that cannot be part of the contact between two polyhedrons and can therefore be eliminated.…”

Section: Introductionmentioning

confidence: 99%

Study on Collision Detection and Force Feedback Algorithm in Virtual Surgery

Luo

2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

The development of virtual reality technology is expected to solve traditional surgical training. The lack of methods has brought revolutionary advances in technology. The virtual surgery system based on collision detection and force feedback can enable the operator to have stronger interaction, which is an exploration of the feature of touch in virtual reality technology. Reality is an important indicator of the virtual surgical system. This article improves the realism of the system from the visual and tactile senses and uses the surrounding ball collision detection and force feedback algorithms to build a realistic surgical platform. In the virtual surgery training system, the introduction of force feedback greatly improves the sense of presence during virtual surgery interaction. The operator can feel the softness and hardness of different tissues and organs through the force feedback device. Virtual reality is an interdisciplinary comprehensive technology that has been widely used in military, film, medical, and gaming fields. Virtual reality can simulate the objective world and display it visually, making people feel immersive. Virtual surgery provides surgeons with a recyclable surgical practice platform and can help doctors perform preoperative rehearsals and predict the results of surgery. The design of collision detection and force feedback algorithms is a prerequisite to ensure the immersion and transparency of the virtual surgical training system. This article mainly introduces the collision detection and force feedback algorithm research in virtual surgery, with the intention of providing some ideas and directions for the development of virtual surgery. This paper proposes two collision detection algorithms, space decomposition method and hierarchical bounding box method, and three force feedback algorithms including spring mass point algorithm, Runge–Kutta method, and Euler method to construct virtual surgery collision detection and force feedback. Experiment with the Overall System Architecture. This paper proves through experimental results that the average collision detection time after the application of the improved collision detection and force feedback algorithm in the virtual surgery system is more than 80.7% less than the traditional method, which greatly improves the detection speed.

show abstract

Computer network security evaluation simulation model based on neural network

Cited by 70 publications

References 15 publications

Retracted: Significance and Possibility of VR Technology Embedded in the Teaching of Ideological and Political Theory Course in Colleges and Universities

Retracted: Significance and Possibility of VR Technology Embedded in the Teaching of Ideological and Political Theory Course in Colleges and Universities

Retracted: Mathematical Model of Yield Forecast Based on Long and Short-Term Memory Image Neural Network

Study on Collision Detection and Force Feedback Algorithm in Virtual Surgery

Contact Info

Product

Resources

About