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An accurate forecast of the area of drought disaster is vitally important for the government to take appropriate measures to prevent disaster. In the current study, a new conformable fractional discrete grey model is applied to study the trend of the area affected by drought disasters. Firstly, the new model, abbreviated as CFDGM(1,1), is proposed with the definitions of the conformable fractional operator and the classical GM(1,1) model. Then the recursive expression of the time response function is obtained by the grey basic form, and the linear system parameters are confirmed by the linear least squares method. Further, the Salp Swarm Algorithm is chosen to determine the optimal conformable fractional order. Finally, the area of drought disaster is studied by the new model and others, where the results show the new model has a good performance among these models.

Discharge for wastewater treatment plays a key role in improving the water quality, thereby guaranteeing living quality of citizens. With high-speed economics growth and economics reforming, total amount of China's discharge of wastewater treatment is sharing high uncertainty, leading to many difficulties in accurate forecasts of discharge of wastewater treatment. Based on grey system theory, the hyperbolic time-delayed term is introduced in this paper to develop a novel forecasting model in order to deal with uncertainties of China's sewage discharge forecasting. The key nonlinear parameter of the proposed model is determined by the Grasshopper Optimization Algorithm. A series of practical numerical cases prove that the proposed model is reliable in comparison with six existing models are used for comparison. Then we apply it to predict the behavior of sewage discharge in China, those results against demonstrating the model our proposed has more satisfactory prediction precision.

This article investigates whether the nonlinear support vector regression method under the Heterogeneous Auto-Regressive model (SVR-HAR) can compete for combination methods in terms of out-of-sampl...

This paper describes the peak, fat tail, and skewness characteristics of asset price via a Lévy process. It applies asymmetric GARCH model to depict asset price’s random volatility characteristics and builds a GARCH-Lévy option pricing model with random jump characteristics. It also uses circular maximum likelihood estimation technology to improve the stability of model parameter estimation. In order to test the model’s pricing results, we use Hong Kong Hang Seng Index (HSI) price data and its option data to carry out empirical studies. Results prove that the pricing bias of EGARCH-Lévy model is lower than that of standard Heston-Nandi (HN) model in the financial industry. For short-term, middle-term, and long-term European-style options, the pricing error of EGARCH-Lévy model is the lowest.

In this paper, we take the advantage of high frequency data to develop option pricing model and select the Realized GARCH model to describe the volatility of assets, use NIG distribution to describe the distribution of underlying assets, and also build the Realized-GARCH-NIG model to price the option. Finally, we obtain the dynamic option pricing model based on the Realized-GARCH-NIG approach. To verify the effect of the dynamic option pricing model based on the Realized-GARCH- NIG approach, this paper provides the empirical analysis between the dynamic option pricing model based on the Realized-GARCH-NIG approach and the B-S option pricing model. The results show that the option value obtained from the dynamic option pricing model based on the Realized-GARCH-NIG approach is more accurate and effective than the B-S option pricing model.

This research studied the duopoly manufacturers’ decision-making considering green technology investment and under a cap-and-trade system. It was assumed there were two manufacturers producing products which were substitutable for one another. On the basis of this assumption, the optimal production capacity, price, and green technology investment of the duopoly manufacturers under a cap-and-trade system were obtained. The increase or decrease of the optimal production quantity of the duopoly manufacturers under a cap-and-trade system was decided by their green technology level. The increase of the optimal price as well as the increase or decrease of the maximum expected profits were decided by the initial carbon emission quota granted by the government. Our research indicates that the carbon emission of unit product is inversely proportional to the market share of an enterprise and becomes an important index to measure the core competitiveness of an enterprise.

In this paper, we used Super-efficient DEA methodology and panel data analysis methods to analysis of the relationship between the performance of state-owned enterprises of Sichan and its shareholding structure. The results showed that: there is no significant correlation between the ownership concentration and corporate performance; there exists significant negative correlation between the proportion of state-owned shares and corporate performance; there is no significant correlation between the proportion of corporate shares and corporate performance. Thus, that moderate control the proportion of state-owned shares will be benefit to the state-owned enterprises of Sichuan.

Countable products of probabilistic normed spaces are introduced and studied. In particular, a comparison is made with the analogous constructions for probabilistic metric spaces.

Probabilistic Normed spaces have been redefined by C. Alsina, B. Schweizer and A. Sklar. But even today, whether the generalized Šerstnev PN space is normable or not is still an open question. In this paper, through applying Kolmogorov's theorem, we will give several sufficient conditions, under which many generalized Šerstnev PN spaces are normable. As the application of our results, we will give two examples which are normable generalized Šerstnev PN space, but not Šerstnev space.