Economic Management Data Envelopes Based on the Clustering of Incomplete DataRead the full article
Mathematical Problems in Engineering is a broad-based journal publishing results of rigorous engineering research across all disciplines, carried out using mathematical tools.
Chief Editor, Professor Guangming Xie, is currently a full professor of dynamics and control with the College of Engineering, Peking University. His research interests include complex system dynamics and control and intelligent and biomimetic robots.
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Mean-Based Breakpoint Selection on Circular Histogram
Circular histogram represents the statistical distribution of circular data; the H component histogram of HSI color model is a typical example of the circular histogram. When using H component to segment color image, a feasible way is to transform the circular histogram into a linear histogram, and then, the mature gray image thresholding methods are used on the linear histogram to select the threshold value. Thus, the reasonable selection of the breakpoint on circular histogram to linearize the circular histogram is the key. In this paper, based on the angles mean on circular histogram and the line mean on linear histogram, a simple breakpoint selection criterion is proposed, and the suitable range of this method is analyzed. Compared with the existing breakpoint selection criteria based on Lorenz curve and cumulative distribution entropy, the proposed method has the advantages of simple expression and less calculation and does not depend on the direction of rotation.
The Improved Constraint Methods for Foot-Mounted Pedestrian Three-Dimensional Inertial Navigation
The foot-mounted pedestrian navigation system (PNS) that uses microelectromechanical systems (MEMS) inertial measurement units (IMUs) to track the person’s position. However errors accumulate over time during inertial navigation solutions, which affects the positioning precision. In this paper, a multicondition zero velocity detector is used to detect the stance phase of gait. Then the errors are corrected in the stance phase and the swing phase, respectively, through the Kalman filter. When pedestrians are going up and down the stairs, the divergence of height will reduce the accuracy of three-dimensional positioning. In this paper, an accelerometer and a barometer are used to obtain altitude variation, and after that the stair condition detection (SCD) algorithm is proposed to correct the height of Kalman filter output and detect the walking state of pedestrians. Through theoretical research and field experiments, these algorithms are studied carefully. The results of the experiment show that the algorithm proposed in this paper can effectively eliminate errors and achieve more accurate positioning.
Study on the Semiactive Control and Optimal Layout of a Hydropower House Based on Magnetorheological Dampers
With the continuous development of hydropower stations, the capacities and the heads of hydro generator units are increasing, and the plant vibration problem is becoming more and more serious. A numerical simulation method for the vibration reduction control of magnetorheological (MR) dampers suitable for large-scale complex structures was proposed. The method is simple and easy to implement, and the semiactive control of the MR damper could be achieved by adjusting the current switch and size. On the basis of a numerical simulation, a mathematical model for the optimal layout of an MR damper device was established. The objective function was the vertical velocity and the vertical acceleration response of the generator floor. The results showed that the proposed semiactive control numerical simulation method could be applied to the vibration control of the hydropower plant structure, and the vertical velocity and vertical acceleration were reduced by 10.96% and 12.90%, respectively, compared with those without structural vibration control. At the same time, the proposed optimized layout method was effective and feasible, and the damping effect of the MR damper could be effectively improved through the optimized layout.
Towards Green Economics and Society: Exploring the Efficiency of New Energy Generation
In recent years, solar and wind energy have been increasingly abandoned due to the blind expansion of the new energy industry. Due to the competitive relationships between different types of new energy, reasonable industrial development planning needs to be implemented to not only save the cost of government subsidies but also clarify the investment direction of social capital. Based on the panel data of OECD countries between 2006 and 2018, the stochastic frontier analysis (SFA) was used to measure the efficiency of new energy generation (NEG) and the influencing factors were analyzed in this paper. Results were as follows: the efficiency of NEG in OECD countries is improving; the efficiency of NEG is positively correlated with technical innovation, government policies, economic level, and education level and negatively correlated with urbanization. Based on the empirical results of this study, problems in the development of the new energy industry have been discussed and suggestions to improve the efficiency of NEG have been proposed.
TOPSIS Hybrid Multiattribute Group Decision-Making Based on Interval Pythagorean Fuzzy Numbers
Aiming at the mixed multiattribute group decision-making problem of interval Pythagorean fuzzy numbers, a weighted average (WA) operator model based on interval Pythagorean fuzzy sets is constructed. Furthermore, a decision-making method based on the technique for order preference by similarity to ideal solution (TOPSIS) method with interval Pythagorean fuzzy numbers is proposed. First, based on the completely unknown weights of decision-makers and attributes, interval Pythagorean fuzzy numbers are applied to TOPSIS group decision-making. Second, the interval Pythagorean fuzzy number WA operator is used to synthesize the evaluation matrices of multiple decision-makers into a comprehensive evaluation matrix, and the relative closeness of each scheme is calculated based on the TOPSIS decision-making method. Finally, an example is given to illustrate the rationality and effectiveness of the proposed method.
Synergy and Correlation Optimization Analysis of Innovation System and Institutional Governance System from the Perspective of Cluster Ecosystem
Innovation and institutional governance are the key enabling factors of cluster ecosystem development. Its synergistic effects play an important role in enhancing ecosystem competitiveness. In this paper, pseudocode language is applied to cluster ecosystem cooperative model reasoning. The coordination and optimization of the innovation system and institutional governance system were studied in a biomedical cluster. Besides, Pearson algorithm was used to test the correlation degree of elements in three Chinese biomedical clusters. The results show that, in Zhangjiang and Nanchang biomedical clusters, the synergistic correlation coefficient between the innovation system and the institutional governance system fluctuates around 0.8. However, in Tonghua biomedical cluster, the synergy correlation coefficient fluctuated around -0.2. The fluctuation range between the two clusters was large. After adjusting the range of order parameters, the rank of synergy trend was Zhangjiang > Nanchang > Tonghua. Finally, further analysis shows that Zhangjiang and Nanchang biomedical clusters can achieve the optimal synergy state by adjusting innovation and institutional governance, but Tonghua cannot. Therefore, the collaboration between the innovation system and institutional governance system provides some reference for the high-quality development of the cluster ecosystem.