Evaluation and Forecasting of Wind Energy Investment Risk along the Belt and Road Based on a Novel Hybrid Intelligent Model

The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road.In order to obtain the scientific and real-time forecasting result,this paper constructs a novel hybrid intelligent model based on improved cloud model combined with GRA-TOPSIS and MBA-WLSSVM.Firstly,the factors influencing investment risk of wind energy along the Belt and Road are identified fromthree dimensions:endogenous risk,exogenous risk and process risk.Through the fuzzy threshold method,the final input index system is selected.Secondly,the risk evaluation method based on improved cloud model andGRA-TOPSIS is proposed.Thirdly,a modern intelligent model based on MBA-WLSSVMis designed.In modified bat algorithm(MBA),tent chaotic map is utilized to improve the basic bat algorithm,while weighted least squares support vector machine(WLSSVM)adopts wavelet kernel function to replace the traditional radial basis function to complete the model improvement.Finally,an example is given to verify the scientificity and accuracy of themodel,which is helpful for investors tomake fast and effective investment risk forecasting of wind energy along the Belt and Road.The example analysis proves that the proposedmodel can provide reference and basis for investment corpus to formulate the investment strategy in wind energy along the Belt and Road.

Investment risk of rural family education: From the persepective of educational cost and income

With the implementation of the policy of popularization of education, rural families make the choice of interests and behavior decisions through the calculation of their own benefits and costs, and gradually become the main body of rural education investment decisions. The relationship between educational cost and income plays a major role in the rural family education investment. Based on the current situation of rural education in our country, this paper focuses on the risk of rural education investment and rural education costs and benefits, and then puts forward scientific, operational measures and suggestions.

Overcoming Investment Risks Chinese investors need to thoroughly understand local conditions before investing in Africa

With abundant labor resources and the increase in policy sup port for economie development and loreign investment, Africa is becoming a new sought-after destination for investment by multinational companics.

The Realization of a Strong Trade Power and China’s Direct Investment in SCO Countries

China’s path to becoming a strong trade power can be divided into three levels:the micro level of promoting factor cultivation,the meso level of achieving industrial dominance,and the macro level of participating in the establishment of the world system.As a feature of globalization,factor flow is the foundation and key to achieve the above three-level goals.In the first stage of reform and opening-up,China complied with the globalization characteristics of factor flow and gathered a large number of capital factors.It is now the second stage of reform and opening-up;that is,the stage of export-oriented investment.International investment may help in the path to become a strong trade power,or it may become an obstacle.The maximization of benefits and evasion of disadvantages are influenced by the grasp of investment risks.Therefore,special attention should be paid to identifying potential risks and controlling risks.

A Method for the Solution of Educational Investment

In order to improve the performance of higher education in the United States, the Goodgrant Foundation intends to donate a total of $100,000,000 (US 100 million) to an appropriate group of schools per year, for five years, starting in July 2016. For this, our team puts forward upon an optimal investment strategy, which includes the schools to invest, the investment amount of each school, and the return due to investment, to solve this problem. Our main idea is as follows. First of all, we choose suitable investment school universities in the United States. Secondly, we use Analytic Hierarchy Process to get the rate of return on investment and venture capital. Thirdly, we establish a venture capital return model. Finally, solving the mathematical model ensures the investment amount of each school and the return due to investment. To implement this strategy, first of all, we obtain the candidate school based on students score card. Then, according to the factor analysis, we analyze the factors which mainly affect the choice of school. Secondly, we employ Analytic Hierarchy Process to get the rate of return on investment and capital risk. In the end, we establish a risk return model to get investment amount for each school, amount of risk and return. In order to ensure the minimum risk and the maximum return, we set up a multi objective programming model and solve it by using the constraint method. We get the result that includes the maximum net profit of the investment and risk loss rate. According to statistical analysis, we can get the overall return of net income within five years. Finally, we choose 320 candidate schools and get the investment amount of each school according to the principle of as many schools as possible. We have proved that the foundation will receive a return of more than 295.363 million in the next 5 years. After-verification, our strategy can be directly applied to the investment field and get good results.

Government Investment in Disaster Risk Reduction Based on a Probabilistic Risk Model: A Case Study of Typhoon Disasters in Shenzhen, China

In recent years, cost-benefit analysis(CBA) has played an important role in disaster risk reduction(DRR)investment decisions, and now increasing attention is being paid to its application in developing countries. This article discusses government investment choices in DRR against typhoon disasters in Shenzhen, China. While the existing literature mainly focuses on disaster mitigation measures such as structural retrofitting, this study proposes a holistic framework of DRR investments in which structural(windproof retrofitting) and financial(insurance premium subsidies and post-disaster relief) are all taken into account.In particular, intermeasure spillover effects are measured and used in CBA. The results show that insurance premium subsidies yield the highest benefit-cost ratio and should be prioritized in investment. Windproof retrofitting comes in second place in terms of the benefit-cost ratio and can be considered when there is a sufficient budget. These results further confirm the need of a holistic review of government DRR investments to derive policy recommendations, while challenges remain in relation to the probabilistic modeling capacity to support CBA.