Abstract This problem is a solar hut photovoltaic cell in the attached and overhead two installation methods, the type of photovoltaic cells and array mode and inverter type optimization design issues. In question 1, since the photovoltaic cells are attached to the roof and exterior surfaces, the direction and angle of the battery are uniquely determined by the direction and angle of the attached surface. The problem is translated to optimize the installation of a certain type on a single surface area (array) of photovoltaic cells, so that the total amount of solar photovoltaic power generation as much as possible, and the unit power generation costs as small as possible, which is a multi-objective optimization problem. The problem can be discussed in the ideal environment in a single surface area of the battery installation optimization program, and then the actual environment of the multi-surface optimization. In the solution to Problem 1, the unit on the south of the roof of the battery at the moment to accept the solar energy formula is generated. The definition of and is the moment of direct radiation intensity, for the moment the sun and the south of the roof of the plane where the angle, for the level of horizontal radiation intensity, for the south of the roof and the horizontal angle, the planefor the plane, the center of the heart, the vertical upward direction is the axis of the positive coordinate system, obtained with the sun height angle , the sun azimuth , red angle, angle and the sun when the relationship is generated. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of electricity generation is 77126 degrees, the economic benefits of 16,488 yuan, the recovery period of 21.3 years. In question 2, because the photovoltaic cells in the roof and the external wall surface can be installed overhead, the panel orientation and tilt will affect the efficiency of photovoltaic cells. Therefore, in the optimization scheme of Problem 1, the orientation and inclination of the panel on each surface are further adjusted to calculate the optimum orientation and inclination of the panel on each surface. The problem can be in the ideal weather environment to establish the sun running and the battery board efficiency model, and then the measured environment test. The optimal orientation of the panel is southward, and the optimal angle with the ground plane is 39.89 degrees. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of generating capacity of 82165.2 degrees, the economic benefits of 18,998 yuan, the recovery period of 13 years. In question 3, by the optimization of the above two issues, in the building to meet the requirements of the hut under the design of the various aspects of the cabin and battery installation, and further optimize the total power generation of the hut, economic benefits. The whole model solver is run in MATLAB7.0.

Abstract This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.

Abstract Nowadays, more and more cars have begun to enter into innumerable families; the family car has become a necessity for Chinese households who have certain purchasing power. However, the ups and downs of oil prices have brought some impact on people's automobile consumption activities. Therefore, after collecting the information of the oil price and family car consumer, carried on through in-depth analysis of the relevant data with reasonable relationship, and then developed a suitable for China's national conditions and finished oil pricing model, thereby the National Development and Reform Commission have proposed the suggestion for China's refined oil pricing mechanisms and promoting the healthy development of new energy vehicles with specific measures. For question 1, through the problem analysis and information access, combined with the past and current situation of the domestic refined oil prices, we analyze the following seven factors: international crude oil prices, China's annual crude oil imports, China's annual crude oil exports, crude oil output in China, China's annual GDP per capita, China's annual consumption of crude oil, the total annual energy consumption in China, all have influence on China's refined oil prices. By monadic linear regression analysis, annual average prices of domestic refined oil products have a certain correlation with the various influencing factors, and then by multiple linear regression way eventually concluded the final relationship between oil prices and the influence factors, which compared with the current price, and make reasonable evaluation model. Through the establishment of various influencing factors and function of time, and using the evaluation model for refined oil product price to make reasonable forecast. According to this model, in order to predict refined oil product price as $122.15 per barrel in 2016. For question two, we basically sums up three key factor which influence the quantity of family vehicle: China's oil product prices, the annual GDP per capita, total road mileage. Through Excel to make the relationship curves of different quantity of family cars against influencing factors, and use Grey Forecasting method to forecast the quantity of family cars. And carries on the residual error test, it is used to conclude that the rationality of the model is highly. The number of private cars of the city of xi 'an is predicts that to 8.302 million vehicles by 2020. For question three, we discussed the relationship between international crude oil prices and domestic exports of crude oil export with domestic refined oil prices, through its multiple linear regressions to get the final pricing model. For question four, according to three previous established models, we proposed China's refined oil pricing mechanism proposal to the national development and Reform Commission: perfect price controls, deeper product market, and integration of resources consideration and environmental protection class tax types, adjust the consumption tax collection and Administration links, and improve the production cost accounting.

Abstract With the development of social economy, the current urban traffic problem is more prominent. In order to solve this problem very well, the idea of establishing intelligent traffic management came into being. The establishment of intelligent traffic management, cannot do without the signal launch and reception. Therefore, how to set up some wireless signal transmitting device in time to travel on the road motor vehicles to send traffic information and how to achieve full coverage of the signal and signal stability is our article to discuss the issue. For the first question, we must separate the motorway and non-motorway from all roads. Motorway lanes are usually straight and long. While the bends are usually just sidewalks or bike lanes (non-motorized lanes). So the 121 road can be clustered analysis, clustering of the two indicators for each road length (the distance between the adjacent points) and the collection point of density (by drawing, you can observe the more curved the denser the road collection point, so the road curvature into the collection point of the intensity), the result of clustering can get 48 motor lanes. And then through regress function regression and data fitting to achieve an approximate description of each type of motor vehicle description model, so that each road in a given latitude (latitude) coordinates to determine the latitude (longitude) coordinates and the corresponding altitude. For the problem of two, according to the meaning of the road to know the signal strength is only related to the distance between the sampling point and the launch device, so you can 'the motor vehicle between the signal reception is relatively close to' this indicator into ' The average of the distance between all the sampling points and the transmitting device is close to '. By reading the data will be latitude and longitude conversion distance length, so that the maximum value as small as possible. The position of the launcher can be obtained by programming by MATLAB. When considering the altitude, only the position of the transmitting device can be changed. (9.7824,56.7720), and the position coordinates when considering the altitude are D (9.7459, 56.7586, 73.5645), and the position coordinate of the signal device is B (9.7824, 56.7720). For question three, note the effect of the original signal device A on the result. We still use the average of the distance between all the sampling points of the road and the launcher to characterize the stability of the signal reception. The average distance of all non-motorized trains to the original signal device A is first determined, and then the average distance of all non-motorized lanes from the new signal device B is set, and the signal acceptance strength of the non-motorized lane can be used to characterize. And then use the same method in question two to determine the location of the new signal transmitter. Finally, the coordinates of the position of the new signal device are E (9.7459,56.7586,73.5645).

Abstract Ebola virus is a potent infectious disease virus that can cause Ebola haemorrhagic fever caused by human and primate. It has high mortality and easy infectivity to form a great obstacle to the steady development of human society. The profound understanding of the virus is particularly important harm. In this paper, a number of mathematical models are established to solve this problem. The software is used to analyze and predict the propagation of Ebola virus. The residual analysis is used to test the model. Finally, the effects of various control measures on controlling the epidemic are analyzed. In order to solve the problem, we will establish the infectious disease model to dynamically describe the spread of the virus in the 'virtual orangutan population'. Considering that the latent population is analyzed in this question, we will improve the model. Join the latent group (), and the migrants are divided into self-healing () and the dead (), to establish a suitable solution to this problem model. According to the relevant data given in the title, differential equations were established. For the second question, this question involves the one-way transmission of the virus across the species, so we can improve the model, on the basis of human contact with orangutans infected groups, the establishment of a one-way model to solve this problem. On the basis of the problem one, the differential equation is established, the model is predicted and tested. In the case of question 3, the number of human susceptible groups is much higher than that of the orangutan infection group by comparing the relevant data with the increase of the cure rate to 80% after the intervention of the outside experts. Therefore, the original data of human populations from experts can be ignored. Since then the virus spreads within a single species, the differential equation can be established according to the model in question 1 and the data values in the virtual human population are predicted. For question 4, the effect of the measures such as the strict enforcement of the various epidemic control measures and the improvement of the drug effect on the control of the epidemic are analyzed by comparing the above-mentioned models with the control measures.