Special issue on multimodal information learning and analytics on cross‐media big data

This special issue focuses on learning methods to achieve high performance multimodal information analysis and understanding under uncontrolled environments in large scale, which is also a very challenging problem. Moreover, it attracts much attention from both the academia and the industry. We hope this topic will aggregate top level works on the new advances in multimodal information from cross-media data. The purpose of this SI is to provide a forum for researchers and practitioners to exchange ideas and progress in related areas. The submitted manuscripts were reviewed by experts from both academia and industry. After two rounds of reviewing, the highest quality manuscripts were accepted for this special issue. This special issue will be published by Concurrency and Computation: Practice and Experience. A tire-ice traction model is established based on a neural network and the finite-element method by Zhang et al.1 Wu et al2 propose a swarm-intelligence–based method, particle swarm optimization algorithm, to handle the elastic parameter inversion problem. An integrated fault diagnosis reasoning strategy based on fusing rough sets, neural network, and evidence theory is presented by Yang and Yu3 using the principles of data fusion and meta-synthesis. Zhang et al4 study the aviation hubs location optimization of express enterprise, primarily using p-median model and greedy dropping heuristic algorithm to solve the initial candidate locations of the aviation hubs by Lingo. Yong et al5 considered the construction of evaluation index system according to the concept and construction situation of Smart City, adopted the five-year statistics of Sichuan Province as empirical data, and this paper applied modeling calculation to draw the objective state of current Smart City construction. Zhao et al6 proposed a method to extract and classify typhoon disaster information from Sina Microblog. The KNN (k-nearest neighbors) algorithm is implemented for microblog classification in order to extract useful information about the real hazards, and an experiment is conducted to tune the parameters in KNN by comparison of outcomes of social media data analysis and the real typhoon situation. Wang and Wu7 propose the novel systematic algorithm paradigm for the electric car data anomaly detection based on association data mining. The correlation matrix is analyzed by Ji et al8 through component analysis method first, to detect the economic implication of the components of correlation matrix. It is found that the biggest driving force of market behavior affects the whole stock market instead of individual stock or plate and the evolution of important plates of the second component relates closely to economic policies. Zhang and Pu9 propose a group of environmental indicators including air quality index, water quality index, and soil quality index that are constructed specifically for evaluating the severity of environment pollution. Guo10 used a probabilistic model checking technique to study the algorithm across different configurations. The mainstream probabilistic model checker PRISM assisted with our final assessment. Simulation study was conducted by Ma et al11 to the plane forms of different courtyard-type residential clusters. An improved FSVM of data classification algorithm (IFSVM) has been proposed by Xie et al.12 Li et al13 propose a framework that provides a shuttle bus solution to satisfy the travel demand of the gathered passengers in rush hours according to their travel history obtained by smartcard data. Lv et al14 propose an energy router microgrid-operation model in which the AC-interface and DC-interface conventional control strategies are replaced by a virtual synchronous generator (motor) and virtual DC motor control strategy such that the energy router can mimic the inertia and damping characteristics of a rotating motor in order to improve the stability of the distributed power network. The evolutionary game theory is used by Yang15 to construct the evolutionary game model of three-party selection different strategies and, through the construction of replicated dynamic equation, solving the evolution stable strategy. Yue and Girma16 studied the mass media affected by the empirical analysis, tried to understand how effects to adolescents' first time contact mass media, and discussed on the mass media using unbalance between the urban and rural areas in developing countries. Based on the research of weight setting in China and abroad, the weight system is designed by Qian17 qualitatively and quantitatively by using the cloud models so that the weight results are close to human cognition and easy to understand and accept. Wang et al18 establish three types of belief degree constrained mathematical models to investigate the problem under the optimistic value criterion, the pessimistic value criterion, and the Hurwicz criterion. The variable probability known/unknown model for information spreading is built by Juan and Bin19 with appropriate parameter assumption. Zhanjun et al20 study the full-duplex relay selection strategy based on a potential game in a cognitive cooperative network under the interference power constraint from secondary users to the primary receivers, the total available transmission power constraint for the secondary system, and the self-interference constraint at each secondary relay. The hierarchal structure, call routing, and bandwidth usage of the multidomain UC system are studied by Shen et al.21 After describing the architecture of the multidomain UC system, a no-worse-than-two-hop query algorithm based on P2P is proposed for interdomain call, and it is showed that 80% of users can finish call query in one hop based on the derived performance formulas. Chen and Hu22 analyzed the chaotic characteristics of Chinese export price index and exchange rate data and studied the predictive ability of the neural network model in exchange rate pass-through prediction. The guest editors would like to thank Prof Geoffrey C. Fox who is the Editor-in-Chief of Concurrency and Computation: Practice and Experience. His help and trust is the most important thing for the success of this special issue. The guest editors would like to thank the reviewers for their high-quality reviews, which provided insightful and constructive feedback to the authors of the papers.