Virtual Reality-Based Fuzzy Spatial Relation Knowledge Extraction Method for Observer-Centered Vague Location Descriptions

Many documents contain vague location descriptions of observed objects. To represent location information in geographic information systems (GISs), these vague location descriptions need to be transformed into representable fuzzy spatial regions, and knowledge about the location descriptions of observer-to-object spatial relations must serve as the basis for this transformation process. However, a location description from the observer perspective is not a specific fuzzy function, but comes from a subjective viewpoint, which will be different for different individuals, making the corresponding knowledge difficult to represent or obtain. To extract spatial knowledge from such subjective descriptions, this research proposes a virtual reality (VR)-based fuzzy spatial relation knowledge extraction method for observer-centered vague location descriptions (VR-FSRKE). In VR-FSRKE, a VR scene is constructed, and users can interactively determine the fuzzy region corresponding to a location description under the simulated VR observer perspective. Then, a spatial region clustering mechanism is established to summarize the fuzzy regions identified by various individuals into fuzzy spatial relation knowledge. Experiments show that, on the basis of interactive scenes provided through VR, VR-FSRKE can efficiently extract spatial relation knowledge from many individuals and is not restricted by requirements of a certain place or time; furthermore, the knowledge obtained by VR-FSRKE is close to the knowledge obtained from a real scene.

On Solution of First Order Initial Value Problems using Laplace Transform in Fuzzy Environment

This study aimed at solving a nonhomogeneous linear first order initial value problem by means of Laplace transform method in fuzzy environment. The conditions for a fuzzy function to be H−differentiable and gH−differentiability are well established. Finally, example is constructed to test the applicability or otherwise of the established results.

FUZZY LIMITS OF FUZZY FUNCTIONS

In this paper, we study the theory of fuzzy limit of fuzzy function depending on the Altai’s principle and using the representation theorem (resolution principle) to run the fuzzy arithmetic.The novelty underlying this theory is that we can provethe convergence of afuzzy function to its fuzzy limit through proving the convergence of its 𝛼-cuts’boundaries to their limits for the membership degree 0<𝛼𝑜<𝛼1≤𝛼≤1.

Comprehensive Evaluation of Salt Tolerance in Rice (Oryza sativa L.) Germplasm at the Germination Stage

Salt stress reduces the yield and quality of rice. It is of great significance to screen out salt-tolerant varieties for the development and utilization of saline land. The study was carried out on 114 rice varieties; first, seven varieties were selected and treated with different salt concentrations (0, 50, 85, 120, 155, 190, 225 mM), and seven traits, including germination energy, germination capacity, shoot length, root length, root number, plant fresh weight, and seedling vigor index, were measured. The salt concentration at which the sodium chloride injury index was 50% of the control was considered the optimal salt concentration. Second, 114 rice germplasms were carried out under an optimal salt concentration (120 mM). Then, principal component analysis, fuzzy function analysis, stepwise regression analysis, correlation analysis, and systematic cluster analysis were carried out on each parameter. There was a significant correlation between each parameter and the D-value, and the correlation coefficient between the seedling vigor index and D-value was the highest. D-value = − 0.272 + 1.335 × STI − SVI + 0.549 × STI − RN − 0.617 × STI-RL + 0.073 × STI − GE, R2 = 0.986. Using this equation, the sodium chloride tolerance of rice in the germination experiment could be quickly identified. This study showed that the seedling vigor index was a reliable parameter to identify the salinity tolerance of rice varieties. Five groups were obtained by classification at a Euclidean distance of 5. There were 8 highly salt-tolerant cultivars, 23 salt-tolerant cultivars, 42 cultivars with moderate salt tolerance, 33 salt-sensitive cultivars, and 8 highly salt-sensitive cultivars. In this study, we found that Riguang was the most salt-tolerant rice variety, and Xiangxuejing15 was the most salt-sensitive variety.

Dimensionless Charts for Predicting the Range of Goaf Roof Caving

In engineering, the method of charts can provide a convenient query for specific engineering problems. To provide the basis for the potential hazard evaluation and rational governance of the goaf, it is necessary to study the quantitative evaluation for the range of goaf roof caving. Undoubtedly, the charts used to visually query the caving range can simplify the workload of the quantitative evaluation. Therefore, the methods of dimensional analysis, numerical simulation, and linear interpolation are introduced to study the dimensionless charts for predicting the caving range. The dimensionless analysis is used to establish the fuzzy function relationship among the influence factors of the goaf roof caving, and the numerical simulation is used to calculate the dimensionless groups in the fuzzy function. Using the linear interpolation, the dimensionless charts in this work can predict the range of goaf roof caving under more working conditions. The results show that the characteristics of the goaf roof caving corresponding to the dimensionless curves are consistent with the actual situation. With the continuous increase of the goaf span l, the dimensionless curves of the caving range experience zero growth, rapid growth, and steady growth. The growth degree varies with the fracture spacing S. Especially in the zero growth phase, the duration of the relatively stable state in the overlying strata of the goaf increases with the increase of fracture spacing S. Moreover, based on the case study of Shirengou Iron Mine, the dimensionless charts obtained in this work can predict the range of goaf roof caving under different working conditions, which indicates the findings of this study have certain guiding significance to the treatment of the goaf.

Extract the network communities based on fuzzy clustering theory

Community detection in complex networks is of great importance in analyzing the interaction patterns and group behaviors. However, the traditional method of community division divide each node in the network into a specific community, while may ignore its internal connection. In this paper, a new strategy that selects a fuzzy function and fuzzy threshold (FF-FT) was presented to discover community structure. Edge dense degree coefficient was introduced to calculate fuzzy relation between nodes, and Fast–Warshall algorithm was used to reduce the complexity of FF-FT. Through the theoretical analysis and the comparison of eight current well-known community detection algorithms on seven real networks and artificial networks with different parameters, the results show that the FF-FT algorithm has a good community detection performance.

Signal Processing and Recognition Technology and Simulation of Radar Communication Integrated System

The integrated radar communication system combines the functions of radar and communication systems. It has attracted wide attention because of its advantages in effectively reducing electromagnetic interference between equipment and reducing equipment volume. However, there is no complete radar communication integrated signal design scheme so that the radar and communication system can operate well at the same time to achieve better detection and communication performance. In order to achieve better results for the integration of radar communication, this article summarizes and analyzes the existing research on integration of radar communication, and summarizes the realization of two design ideas of superimposed signal and single signal. The basic system composition of pulse radar and continuous wave radar, the working mechanism of radar speed and distance measurement and the basic composition of communication system are described. Research has proved that through the integration of radar communication, signal processing and identification are greatly improved, the signal transmission strength is more than 30% stronger than that without integration, and the transmission distance is 20% higher. Moreover, there are also great differences between the different integration methods. The fuzzy function used in this article is better than other experimental methods. This shows that the integrated radar communication system is the trend of future research on signal processing and recognition.

A Study on Mental Health Assessments of College Students Based on Triangular Fuzzy Function and Entropy Weight Method

The fuzziness and uncertainty of mental health assessments for college students lead to considerable challenges for psychological counselors in universities. Therefore, this paper proposes a method based on triangular fuzzy and entropy weights to evaluate the mental health of college students. This method not only reduces the interference of human factors but also realizes the quantification of the results of mental health evaluations among college students. The triangular fuzzy function and entropy weight were used to comprehensively evaluate the mental health of college students. The feasibility and rationality of the proposed method were verified by experiments on individual students and actual data from different colleges.