In order to formulate water allocation schemes under uncertainties in the water resources management systems, an inexact multistage stochastic chance constrained programming (IMSCCP) model is proposed. The model integrates stochastic chance constrained programming, multistage stochastic programming, and inexact stochastic programming within a general optimization framework to handle the uncertainties occurring in both constraints and objective. These uncertainties are expressed as probability distributions, interval with multiply distributed stochastic boundaries, dynamic features of the long-term water allocation plans, and so on. Compared with the existing inexact multistage stochastic programming, the IMSCCP can be used to assess more system risks and handle more complicated uncertainties in water resources management systems. The IMSCCP model is applied to a hypothetical case study of water resources management. In order to construct an approximate solution for the model, a hybrid algorithm, which incorporates stochastic simulation, back propagation neural network, and genetic algorithm, is proposed. The results show that the optimal value represents the maximal net system benefit achieved with a given confidence level under chance constraints, and the solutions provide optimal water allocation schemes to multiple users over a multiperiod planning horizon.

In order to solve the optimization problem of selecting the decision with maximal chance to meet the Sugeno event in Sugeno environment, dependent-chance programming on Sugeno measure space is proposed, which can be considered as a generalized extension of the stochastic dependent-chance programming. Firstly, the theoretical framework of dependent-chance programming on Sugeno measure space is established. Secondly, a Sugeno simulation-based hybrid approach, which consists of back propagation neural network and genetic algorithm, is presented to construct an approximate solution of the complex dependent-chance programming models on Sugeno measure space. Finally, some numerical examples are given to illustrate the effectiveness of the approach.

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With the continuous development of modern society, people's demand for the network is also rising. Because of its powerful function, wide coverage and other advantages, people in modern society have higher and higher utilization rate of the network, and many things are realized with the help of the network. At the same time, some new business based on the network is emerging. The rapid development of network technology makes many people rush for it. This paper mainly studies how to improve the cache technology, reasonable and effective allocation of resources, so that people can get a better experience. This paper studies the suitability evaluation of tourism development of regional cultural heritage resources by using Delphi method and AHP analytic hierarchy process, and infiltrates the evaluation items into various levels, such as natural environment conditions, social and economic conditions, resource combination levels and so on. Through the analysis and comparison of different geographic information, we can clearly understand whether the region is suitable for tourism and the spatial differences of some regions. To a certain extent, it lays the foundation for the future development of cultural heritage tourist attractions and the spatial analysis based on GIS, which is consistent with the tourism suitability evaluation index in the field of regional cultural heritage. When comparing the data with different measurement levels, we can directly determine the characteristics of the spatial differences of different cultural heritage resources, which depends on the value of resources and location conditions of a specific region.