The rise of FinTech has been meteoric in China. Investing in mutual funds through robo-advisor has become a new innovation in the wealth management industry. In recent years, machine learning, especially deep learning, has been widely used in the financial industry to solve financial problems. This paper aims to improve the accuracy and timeliness of fund classification through the use of machine learning algorithms, that is, Gaussian hybrid clustering algorithm. At the same time, a deep learning-based prediction model is implemented to predict the price movement of fund classes based on the classification results. Fund classification carried out using 3,625 Chinese mutual funds shows both accurate and efficient results. The cluster-based spatiotemporal ensemble deep learning module shows better prediction accuracy than baseline models with only access to limited data samples. The main contribution of this paper is to provide a new approach to fund classification and price movement prediction to support the decision-making of the next generation robo-advisor assisted by artificial intelligence.

Water distribution networks (WDNs) is crucial to ensure social operations and economic activities. However, WDNs are highly sensitive and vulnerable to disasters. The aim of this study is to mitigate the catastrophic consequences of cascading failures in WDNs. A flow-based WDN cascading failure model is built. The extended multi-objective particle swarm optimization model is developed to resist cascading failures and improve resilience. This model takes pipe diameter as the decision variable to minimize cost and maximize pressure deficit. Water balance, pressure, and standard pipe diameter are the constraints. The classical optimal scenario (COS) and the cascading failure scenario (CFS) are simulated. The model is applied to a small and medium-sized benchmarked WDN. Results show that the extended PSO can find the optimal solution on the benchmarked WDN. The Pareto fronts are obtained. Compare to the Pareto fronts between COS and CFS, the pressure deficit under CFS is significantly reduced, and the cost is reduced while the same pressure deficit increased. Different tolerance parameters are tested. The small network is not sensitive to the tolerance parameter, but the medium-sized network is sensitive. The model evaluates a variety of conflicting goals, which help designers and water managers resist cascading failures in WDNs.

<abstract> <p>Using textual analysis, this paper divides green finance into green initiatives and green business activities. The former discusses whether environmental initiatives shall be signed, while the latter explores whether various emerging green commodities and services are provided. This paper investigates the influence of corporate size, the degree of internationalization, profits and competitiveness on the engagement degree of green finance, according to data collected from 410 Chinese listed companies on the Shanghai Stock Exchange. The results show that corporate size exerts a positive influence on green initiatives, and that the degree of internationalization, profits and corporate competitiveness of an enterprise each have a significant effect on green business activities. In addition, profits have a negative influence on green business activities. This paper provides insights and suggestions for developing green business activities in China.</p> </abstract>

Aiming at the problem that the uncertainty of resource allocation can lead to the increase of the parallel iteration time of the coupled task set, a parallel iteration time optimization model under the uncertainty of resource allocation was constructed based on the analysis of the resource allocation uncertainty and iteration time model in the parallel iteration. Then the analytic hierarchy process (AHP) was introduced, and by determining the AHP model and the resource allocation matrix, an improved parallel iteration time optimization model under the uncertain resource allocation was constructed. Combined with an example of product development process, application research was carried out by applying the MATALB software, thereby verifying that the improved optimization model can reduce the parallel iteration time of the coupled task set under uncertain resource allocation. This research provides a reference for optimizing resource allocation and reducing time in product design and development.