Accurate prediction of forthcoming oxygen concentration during waterless live fish transportation plays a key role in reducing the abnormal occurrence, increasing the survival rate in delivery operations, and optimizing manufacturing costs. The most effective ambient monitoring techniques that are based on the analysis of historical process data when performing forecasting operations do not fully consider current ambient influence. This is likely lead to a greater deviation in on-line oxygen level forecasting in real situations. Therefore, it is not advisable for the system to perform early warning and on-line air adjustment in delivery. In this paper, we propose a hybrid method and its implementation system that combines a gray model (GM (1, 1)) with least squares support vector machines (LSSVM) that can be used effectively as a forecasting model to perform early warning effectively according to the dynamic changes of oxygen in a closed system. For accurately forecasting of the oxygen level, the fuzzy C-means clustering (FCM) algorithm was utilized for classification according to the flatfish’s physical features—i.e., length and weight—for more pertinent training. The performance of the gray model-particle swarm optimization-least squares support vector machines (GM-PSO-LSSVM) model was compared with the traditional modeling approaches of GM (1, 1) and LSSVM by applying it to predict on-line oxygen level, and the results showed that its predictions were more accurate than those of the LSSVM and grey model. Therefore, it is a suitable and effective method for abnormal condition forecasting and timely control in the waterless live transportation of flatfish.

As an emerging productive service industry, the character of logistics industry determines the technical innovation activities to consider whether it can improve the operational efficiency of upstream and downstream enterprises in the supply chain. From the perspective of supply chain based on technological innovation mechanism and technological innovation strategy theory, combined with the characteristics of logistics equipment, the conceptual model of the factors affecting the technological innovation of logistics equipment manufacturers is constructed from the aspects of market demand, environment, positive incentives, technological innovation strategies and characteristics of downstream logistics enterprises. Based on this, the corresponding hypotheses are put forward and verified also the intensity of each influencing factor on the technological innovation of logistics equipment manufacturers is analyzed.

On the basis of the principle of order parameters of synergy, a synergy model of the financial-technological-industrial collaborative innovation system in the Yangtze River Economic Belt was constructed. Panel data for the financial structure, technological innovation, and industrial innovation in the Yangtze River Economic Belt for the period from 2011 to 2016 were used to analyze the degree of synergy within each subsystem of the innovation system and between the subsystems and measure the corresponding levels of synergy. The research showed that the financial-technological-industrial subsystems in the Yangtze River Economic Belt were basically in an orderly state, and the Jiangsu subsystem exhibited the best synergy, followed by Shanghai and Zhejiang, whereas that of Yunnan was poor. The overall economic cooperation of the Yangtze River Economic Belt is not ideal, and the level of synergy fluctuates greatly.

The quality of urban development is an important symbol reflecting the level national modernization. Here, we examine the cities in the Bohai Rim coastal area and establish an urban development quality index system based on four aspects of urban development: residents living, humanistic environment, environmental protection, and economic development. We then used the CRITIC-TOPSIS analysis method to evaluate the coastal node cities. Based on our results, we found that the quality of urban development in the Bohai Rim coastal can be represented by a "pyramid", the distribution of urban development quality is unequal, and the node cities are divided into five grades. We hope that our novel approach could be helpful for the assessment of urban development quality.