Ebook: Applied Mathematics, Modeling and Computer Simulation

This book contains the selected papers from the 2022 International Conference on Applied Mathematics, Modeling and Computer Simulation (AMMCS 2022), which was held on August 13, 2022. It provides scholars and researchers with an effective medium for communicating important recent developments in their areas of specialization to colleagues and to scientists in related disciplines. More than 150 participants were able to exchange knowledge and discuss the latest developments at the conference.

The book contains 127 peer-reviewed papers, selected from more than 200 submissions and ranging from the theoretical and conceptual to strongly pragmatic and addressing industrial best practice. It covers Mathematical Modelling and Application, Engineering Applications and Scientific Computations, Simulation of Intelligent Systems.

The book shares practical experiences and enlightening ideas and will be of interest to researchers and practitioners in applied mathematics, modeling and computer simulation everywhere.

Prof. Chi-Hua Chen, Fuzhou, University, China

Prof. Andrea Scapellato, University of Catania, Italy

Prof. Alessandro Barbiero, University of Milan, Italy

Prof. Dmitry G. Korzun, Petrozavodsk State University, Russia

In order to improve the ride comfort of the bus and the roll stiffness of the bus body when turning, a coaxial interconnected hydro-pneumatic suspension model was established. In this paper, the structure and working principle of the single cylinder type hydro-pneumatic spring and the coaxial connected hydro-pneumatic suspension are introduced, and on this basis, the mathematical model is established. By comparing the simulation analysis, it shows the superiority of the ride comfort and anti-roll with the air spring.

By defining global equity and other mathematical methods, this paper constructs an equity distribution system for the asteroid mining industry which uses AHP and weight-based Topsis to construct a global equity evaluation model. This model obtains the equity coefficients of 117 countries, which can provide a thorough guiding reference in the distribution of benefits to some degree. Then, the concept of the relative deprivation coefficient is added to the model to adjust the equity of distribution. The model assigns different priorities to countries in the asteroid mining industry, speeding up mining efficiency while improving equity. What’s more, we also combine the models to construct a standard world framework to show the change of global equity coefficient in a century in the phenomenon of ideal asteroid mining. Based on the model we formulate, we conduct an experiment and visualization to show the worldwide change of equity coefficients.

Forest farms in Northeast China play an important role in achieving carbon peaking and carbon neutrality in the region. Balancing the various values of forests is important to achieve sustainable development in the region. In this paper, a CO2FIX model for calculating forest carbon sequestration is first established. Then an evaluation result-oriented decision model (ERDM) is established. Evaluate the carbon sequestration value, economic value and ecological value of forests, and propose oriented policies for the values with lower scores. Then a multi-objective planning process is established with the goal of maximizing the sum of various forest values, and the oriented policy directly affects the constraints. The results of multi-objective planning provide quantitative indicators for forest management plans. After testing, the above decision-making scheme has achieved the benign development of forest farms in Northeast China in the process of simulated management.

With the accelerated pace of national modernization, the issue of sewage discharge in urban and rural industrial parks has attracted more and more attention. Disorderly discharge of industrial sewage by some enterprises has seriously damaged the urban and rural environment. This paper realizes the real-time monitoring of the water quality of the water outlet. In order to realize this system, firstly design a three-dimensional model of a hydroelectric power plant and simulate the water pressure of the turbine, use the GPRS module and STM32 main control chip to control the electric ball valve, and control the electric ball valve through the single-chip microcomputer to block the sewage in time. The high-level wind power generation in the plant is used to generate electricity for the cloud platform server, the GPRS module is used to upload data to the cloud platform, and the BDS positioning module is used to achieve real-time and accurate water quality monitoring in urban and rural industrial parks.

Low carbon development has become the theme of today’s social development, which foundation was renewable energy.For example: photovoltaic power generation, wind power generation, hydropower generation and so on.One of the representatives of new energy is photovoltaic power generation. After a long period of development, photovoltaic power generation technology has become more and more mature. For improved solar cell stability, photoelectric conversion efficiency, low cost and data security of energy information. 3D printing system and method of organic polymer solar cell device based on blockchain was rough design. 3D printing technology could be used to replace traditional manufacturing technology to complete the printing and manufacturing of solar cell devices. In order to meet the requirements. First, Modeling solar cell structure according to customer requirements, and then process simulation and performance analysis, 3D printing manufacturing after reaching the standards.For data security combining blockchain technology with 3D printing technology, the data security problem of 3D printing could be solved. Blockchain technology has been use to data structure to verify and store data. Blockchain could be considered as a distributed ledger which was decentralized, non-tamperable, traceable, and maintained by multiple parties. By applying the features of blockchain technology such as data encryption, time stamping, and distributed consensus to 3D printing technology, combined with the cloud platform, the cost and stability of 3D printed solar cell devices would be further improved.

Water is precious resources for industrial and agricultural production. It is necessary to accurately measure the water flow. And, the accuracy of flow measurement is very critical to avoid safety accidents in some industrial productions. The sound alarm for flow measurement and control water flow was designed. Many sensors and buzzers were used in the design system. Through the water flow control modeling and simulation, the adaptive control threshold could be set according to different parameters of the system, make the system not only carries out fuzzy automatic control, and also uses cloud platform remote control. When a parameter was abnormal, it could send out an audible alarm, and the user could monitor remotely through the mobile terminal. The design could be applied not only to large-scale industrial production, agricultural irrigation, but also to small household control fields.

The prioritized random access mechanism has been researched in this paper. The current situation of large-scale node multiple access in the Internet of Things leaded to channel congestion and increased blocking rate. In M2M communication, there were a large number of nodes trying to RA. In this case, serious physical random access channel overload would occur, making it even difficult to access the network. Nodes spent a lot of time accessing the network, and even given resource management schemes could not guarantee acceptable end-to-end latency meet QoS guarantees. So, the traditional method has greater limitations in supporting different QoS in M2M communication, It would also have an unimaginable impact on the web, Therefore, it was necessary to propose a scheme to reduce the access delay while ensuring the success rate, The current priority-differentiated random access mechanism needed to consider how to match with the new features of M2M services. The reasonable random access scheme and efficiently manage the resource and allocated the channel were designed in the system where the traditional H2H service and the new M2M service coexist. The weights of different services were obtained by modeling and simulation. Therefore, by setting different threshold detecting preamble index matching service type and calling different back-off indexes to reduce the access collision, so as to optimize the random access mechanism. This study could make the node indicate its priority in the access process, and reduced the conflict and access delay. Under 5G communication technology, this solution would be widely used.

The simulation system of the new marine simulator is established based on the software Videotrace and VRML language. Many kinds of high and new technologies such as 3D modeling, calibration modeling of the cloud server, the interactive design of the virtual scene have been used in the simulation platform of virtual marine simulator. The new simulation system has further development and excellent interaction function. At the same time, research of virtual marine simulator is carried out for the purpose of improving the development of navigation simulator and the training model in the compound seafarers.

Minimum spanning tree (MST) has been devised for non-local cost aggregation to solve the stereo matching problem. However, the cost aggregation is employed directly from leaf toward root node, then in an inverse pass without considering any decision rules. And a small amount of noise is also existed in stereo image pairs. Both of the limitations often lead to failure in achieving more competitive results. This paper presents a novel stereo matching algorithm using forward-backward diffusion and pruning-based cost aggregation. In “forward-backward” process, the raw image pairs are smoothened on a horizontal tree structure as well as retaining image edges sharp. During cost aggregation, the MST where a complete graph involves the whole image pixels is cut off self-adaptively when the depth edge information is referred to. Each node in this tree receives supports from all other nodes which belong to similar depth regions. Meanwhile, an enhanced edge similarity function between two nearest neighboring nodes is formulated to deal with the small-weight-accumulation problem in textureless regions. Consequently, the cost volume can be well aggregated. The proposed method is demonstrated on Middlebury v.2 & v.3 datasets and can obtain good performance in disparity accuracy compared with other five MST based stereo matching methods.

The safety of transmission lines is affected significantly by wind deflection characteristics. In the present study, the effect of transmission lines arrangement on wind deflection characteristics is investigated, where the distance between transmission lines is different. At low Re, the effect of the distance between transmission lines on C_Drag and C_Lift is significant. C_Drag of the left two transmission lines are the same, which are larger, while C_Drag of the right two transmission lines are smaller. C_Lift of the top two transmission lines are larger, while C_Lift of the bottom two transmission lines are smaller. With the distance between the transmission lines increasing, the interaction between the transmission lines becomes weak, both C_Drag and C_Lift of the four transmission lines approach to those of the single transmission line.

Food safety has always been an important concern of people. Under the rural revitalization strategy, as the main force in the process of agricultural and rural modernization agricultural product quality and safety control of agricultural leading enterprises is the focus of work. With the gradual formation of well-off and affluent consumption structure, consumers have produced “from farmland to table” agricultural product quality and safety requirements. However, in recent years, there are still omissions and deficiencies in the quality and safety control of agricultural products. By studying a large number of literature, this paper uses big data processing technology to crawl web data, this paper conducts research and analysis on the quality safety and control status of the whole industrial chain of agricultural products. Based on the whole industrial chain of agricultural products, from the perspective of farmers, leading agricultural enterprises, governments, dealers, consumers and other subjects, LDA theme analysis model is used to identify and collect the quality and safety control factors of the whole industrial chain of agricultural products. This paper puts forward the improvement countermeasures and suggestions of agricultural product quality and safety control under the traceability system, which provides a theoretical basis and guidance for agricultural leading enterprises to ensure the quality and safety of agricultural products.

As the approach of fifth-generation (5G) era, the auto industry has received good development opportunities, which is one of the industry that has benefited most from 5G. Based on the powerful communication of 5G NR, all the information of vehicle running performance can be uploaded to the cloud. With the help of cloud computing, multiple internet of vehicles (IoV) applications come into existence. In this paper, the performance verification methods for typical IoV applications will be introduced in more details. Under each application scenario, we first determine a suitable traffic model, and further analyze how some key performance indicators (KPI) vary as the number of vehicles increases.

With the increasing proliferation of malicious code, the camouflage of malicious code is more difficult to cope with. Traditional malicious code detection techniques based on byte comparison have limited accuracy. Detection techniques based on traditional machine learning are highly dependent on feature selection, and the quality of the classifier directly affects the detection results; this increases the difficulty of accurately distinguishing the types of malicious code. To address these problems, a deep neural network-based malicious code detection method is proposed in this work. First, the code binary file is transformed into a corresponding gray-scale image, and then the enhanced RGBA image is formed by using an image enhancement scheme based on information entropy and code file structure. Afterwards, a convolutional neural network is used. The network extracts high-dimensional features of the enhanced code image, detects the malicious code, and classifies the malicious code. The experimental results show that the proposed method distinguishes malicious code with 98.83% detection accuracy. Its classification accuracy is 97.74% (with positive samples) and 98.85% (without positive samples). These high levels of accuracy are suitable for current complex and changeable malicious code environments, and can provide a new solution for the current malicious code detection field.

A large number of ship-borne mast failure accidents show that fatigue damage is the biggest hidden danger of mast structure. This paper analyzed the major failure factors and prevention method of girth weld fracture of a mast based on finite element method and test method. The results show that the structure where stiffeners are welded to the base of the mast retain high levels of welding residual stress, and therefore, reduce fatigue resistance of the mast. Furthermore, multi-directional wind loading can lead to the stress exceeding the fatigue strength in the girth weld area of the mast which promote initiation of fatigue crack. The effect of the thickness of the mast on the stress level of the mast is analyzed, and the results show that increasing the thickness of the mast can effectively reduce the stress level in the girth weld area, that is, the stiffness of the mast structure increases. The finite element analysis is validated by comparing the results of finite element calculation results and tests.

For the current problems of separation of flight control and gripping control of the gripping UAV and redundancy of UAV degrees of freedom and robotic arm degrees of freedom. In this paper, the characteristics of multi-rotor UAV with high mobility and multiple degrees of freedom are used to replace the traditional mechanical gripper structure. At the same time, binocular vision technology is used for target information acquisition, the target position is converted into UAV flight attitude control commands, and conduct mathematical modeling and analysis of a multi-rotor grasping UAV.

The removal of disabled satellites requires the chaser satellite to perform approach tasks. The uncertainties of chaser inertial parameters and thruster output force affect the control accuracy, which may lead to a collision. In this paper, a modified least square method is proposed to refine the model of the chaser satellite, and then the identified parameters are then applied to the controller to reduce control error. Firstly, an optimal trajectory is planned and then performed in space, after which the state sequences are transmitted to the ground. Next, in order to refine the satellite model, a modified least square method is carried out to identify the modification ratio of thrusters, in which two extra limits are introduced to enhance convergence. One is the maximum fix value per step, the other is the total fix upper limit. Finally, the chaser controller is integrated with the modification value. Simulation results indicate that the proposed method enhances the process of convergence and significantly reduces the remaining error.

Because of the importance of military expenditure to the security of nation, it has been a crucial and hot point in military research for decades. In the paper, we develop co-movement network of international military expenditure with the empirical mode decomposition method and Granger causality test. The results demonstrate that the most influential nations on different time scales are similar despite that the short-term components are disturbed. As the time scale increases, the pattern tends to be more clarified that the nations with developed economy or powerful military force, e.g., UK and USA are the most influential countries in co-movement of military expenditure. our paper provides a novel network approach to study the co-movement military expenditure path among nations from short- and long-term time-scale, where affectees and influencers are distinctive.

To measure the cooperation effect between civil aviation and high-speed rail, the paper quantifies the impact of the hub integration between airports and high-speed rail stations on airport passenger throughput and proposes a hub-integrated model based on the difference in differences method. Airports in China mainland with complete annual passenger throughput from 2007 to 2018 are selected into the sample. And for the requirements of the non-randomized controlled trial, those which integrate with stations are divided into the treated group and the rest are in the control group. Then a balanced panel dataset about all chosen airports and the cities where those are located is created for econometric analysis. To control the influence of confounding factors and satisfy the parallel trend assumption which is the basic condition of the difference in differences method application, propensity score matching is carried out by using the nearest neighbour matching within a caliper. Results show that the annual passenger throughput of the treated airports increases by 17.5% on average than before. Since most of the new airport passengers are transferred to or from high-speed rail stations, it is beneficial for both transport modes to construct the hub integration.

Using parameterized dynamic Bingham model to describe the relationship between active control actuator movement and damping force. SIMULINK emulation module of nonlinear actuator movement characteristics and compared with test data has been achieved by adopting MTLAB. According to the active system of displacement, velocity, acceleration and the desired damping force, the control current inverse model has been obtained based on fuzzy control theory. The validity and correctness of the simulation model are verified by the test results of variable current inverse. Fixed frequency excitation and real flying helicopters floor vibration data are adapted respectively to simulation, and the damping effect of the control system is obtained through simulation analysis.

This paper presents a finite-time formation control scheme that can deal with linearly parametric uncertainties and unknown bounded disturbances. More precisely, the sliding surface is defined based on only the local relative measurements, yields the smooth manifold related to the control problem, the distributed controllers are designed without and with the uncertainties and external disturbances that ensure the finite-time convergence, and the robust control part is derived relies on the estimation technique according to the properties of smoothness and input saturation. To obtain the better performance of multiagent systems, a feasible boundary layer for saturation function is selected in the proposed control algorithm. It is shown that the proposed control can greatly eliminate the chattering effect, and the global uniformly ultimately bounded is ensured. Finally, simulation results are presented to illustrate the dynamical performance of the proposed robust formation control scheme.

When two or more radars with separated space positions and overlapping coverage are used to detect the targets, a radar network is formed. Radar networking can complete data information sharing, improve the reliability of early warning, identification, positioning and detection functions, and improve system functions. Due to the differences in frequency band, platform, system and polarization form of each radar, the deployment process is highly comprehensive. In this paper, a calculation model based on radar detection probability is established for optimal deployment of netted radar. The model takes into account the number of pulse accumulation of pulse radar. The PSO algorithm with variable weight is used to quickly calculate the optimal solution. The best deployment scheme maximizes the detection probability of the netted radar. The simulation results show that the model can describe the detection probability of the netted radar against targets at different distances, and it has important reference value for the optimal deployment of the actual radar network.

A green energy certificate transaction, as one of the ways to meet China’s renewable energy quota system, is a virtual transaction through the renewable energy trading system. Different from the market mechanism of only one transaction in the past audit cycle, this paper establishes an agent-based renewable energy system with multi-period trading according to the existing green energy certificate trading policy. With simulation of a period of audit of green spot multi-period transactions, the agent of limited rationality makes it in the pursuit of their utility under the premise of interaction. The experiment observes the utility level of agents under different trading strategies, verifies the influence of different policy behaviors on the market, and obtains the market equilibrium state. The conclusion shows that there is a serious green certificate premium in the early stage of the market. After adjustment by fines, the green certificate price of 0.05-0.08 yuan can maximize social welfare and stimulate the enthusiasm for individual purchases.

In this paper, we mainly discuss the Lotka-Volterra competition model with Robin boundary and free boundary conditions, and discuss the long time asymptotic behaviour of solutions in the weak-strong competition case. When g_∞<∞ the inferior competitor p can not spread successfully as t→∞. While for the superior competitor q, there are two cases: One is when g_∞≤ R^*, q will die out eventually; the other is when g_∞>R^*, q can spread successfully. However, when g_∞=∞, both p and q have upper and lower bounds.

In this paper, a software confidence evaluation model based on software fault tree analysis and deep auto-encoding network is established to calculate the confidence of rocket fire control software. First, a fault tree is established accroding to the common architecture of rocket fire control software, and a metric set for rocket fire control software is constructed. Second, an autoencoder is used to perform feature dimension reduction and confidence estimation on historical data, so as to calculate top-event occurrence rate, that is, the probability of the software failure. Finally, an example analysis of the propoded method was carried out, and compared the rusults with the results of the traditional exponential model. The case study show that the confidence evaluation model established in this paper is effective, which can be used for the confidence evaluation of rocket fire control software in the engineering development process. And it can also be extended to other types of software.