Article of the Year 2021
Complex Urban Systems: Challenges and Integrated Solutions for the Sustainability and Resilience of CitiesRead the full article
Complexity publishes original research and review articles across a broad range of disciplines with the purpose of reporting important advances in the scientific study of complex systems.
Chief Editor, Prof Sayama, is currently researching complex dynamical networks, human and social dynamics, artificial life, and interactive systems while working at Binghamton University, State University of New York.
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Corporate Bond Pricing Model with Interaction between Liquidity and Credit Risk
This study derives a liquidity and credit risk-adjusted capital asset pricing model and investigates the model using the data set in China's corporate bond market. Our research shows that the channels through which liquidity risk affects corporate bond return are individual bond liquidity risk, the interaction between individual bond liquidity risk and market liquidity risk. The channels through which credit risk affects corporate bond return are individual bond credit risk, the interaction between individual bond credit risk and market credit risk. The main channel through which the interaction between liquidity risk and credit risk affects corporate bond return is the interaction between individual bond liquidity risk and market credit risk. The model reveals the impact mechanism of individual risk and market risk on bond return and explains why the interaction between liquidity risk and credit risk affects bond pricing.
Suspension System Control Based on Type-2 Fuzzy Sliding Mode Technique
This paper presents a new method of intelligent control for vehicle suspension. First, the suspension system is modeled with all the details, and then based on the obtained model, the sliding mode control is designed for it. The controller parameters and coefficients are calculated and updated by a type-2 fuzzy system. The chattering phenomenon is eliminated with a unique technique. In order to evaluate the performance of the proposed control system, two-model uncertainty of the road is applied. Simulations have been performed for both active and passive modes. The simulation results show the high efficiency of the proposed control system.
Robust Trajectory Tracking of Uncertain Systems via Adaptive Critic Learning
This study develops an adaptive dynamic programming (ADP) scheme for uncertain systems to achieve the robust trajectory tracking. In this framework, the augmented state is first established via combining the tracking error and reference trajectory, where the robust tracking control problem can be resolved using the regulation control strategy. Then, the robust control problem of uncertain system can be represented as an optimal control problem of nominal system, which provides a new pathway to address the robust control problem. To realize the optimal control, the derived Hamilton–Jacobi–Bellman equation (HJBE) is solved by training a critic neural network (CNN). Finally, two innovative critic learning techniques are suggested to calculate the unknown NN weights, where the convergence of NN weights can be guaranteed. Simulations are carried out to demonstrate the effectiveness of the proposed method.
Complex Management Countermeasures of Postgraduate Education Quality Based on Comparison of International Training Models
Graduate students are an important engine of national and regional development and the dominant force of contemporary scientific and technological innovation. It has become the historical mission of high-level research universities to provide strong talent support for the construction of innovative powerful countries with human resources. This investigation performed a systematic and comparative analysis of international postgraduate training models. The whole process of multidimensional training countermeasures and suggestions were proposed. Those specifically included updating the training concept, optimizing the curriculum structure, innovating teaching methods, strengthening practical training, strengthening the responsibility of the tutor, and expanding the international vision. After investigation and analysis, this research pointed out that the conditions of establishing and perfecting the examination system, evaluation mechanism, and incentive measures related to postgraduate education were guaranteed. Multiple measures to improve the quality of graduate students have certain reference significance for the current graduate education.
An Aggregating Prediction Model for Management Decision Analysis
Facing an increasingly competitive market, enterprises need correct decisions to solve operational problems in a timely manner to maintain their competitive advantages. In this context, insufficient information may lead to an overfitting phenomenon in general mathematical modeling methods, making it difficult to ensure good analytical performance. Therefore, it is important for enterprises to be able to effectively analyze and make predictions using small data sets. Although various approaches have been developed to solve the problem of prediction, their application is often limited by insufficient observations. To further enforce the effectiveness of data uncertainty processing, this study proposed an aggregating prediction model for management decision analysis using small data sets. Compared with six popular approaches, the results from the experiments show that the proposed method can effectively deal with the small data set prediction problem and is thus an appropriate decision analysis tool for managers.
Differential Trust and Hierarchical Regulation: A Study of the Effectiveness of Rumor Refutation on Government Micro-Blogs—Analysis Based on 1290 Rumor Refutation Messages
Purpose/Significance. This study aims to explore the differences in the effectiveness of rumor refutation dissemination on government micro-blogs and to identify factors that may lead to such differences, so as to provide reference for the management of emergencies and to improve the effectiveness of rumor refutation. Methodology/Procedure. Using Octopus software to collect data from thirty government micro-blogs, the number of retweets, likes, and comments were used as indicators of the effectiveness of refutation dissemination and different levels of government micro-blogs were used as moderating variables to construct a regression model of the effect of content features and text features on refutation dissemination. The regression model was constructed to test the moderating effects of micro-blog content and text features on the effectiveness of micro-blog refutation. Results/Conclusions. The empirical results show that whether a micro-blog is from the region or not and whether a micro-blog has a title or not have a significant effect on the effectiveness of micro-blog refutation dissemination. Therefore, refutation strategies such as combining layers, giving equal importance to content and form, and focusing on originality can be adopted to enhance the refutation effect of government micro-blogs.