Search

A hybrid model is proposed which is a combination of MLRM (Multiple Linear Regression Model) and GM (Gray Prediction Model). The paper conducts a line loss rate forecast of the grid, and develops a kind of forecasting software for the line loss managers of grid enterprises to realize the analysis and forecast of factors which impact the daily loss line rate. Finally, do simulation examples with line loss rate data of a city using the software. The results demonstrate that the models selected in the software have good feasibility in line loss rate forecasting, and can overcome the adverse effects of factors on the model, improve the accuracy of prediction and provide the basis for the scientific and reasonable loss reduction plan.

The purpose of present study is to build a multiple linear regression model using biomechanical theory to assess the relationship of pulse wave velocity (PWV) with blood pressure, height and age. By testing the PWV, blood pressure, height, weight of 164 female adults aged above 45 and existing data, the author constructed a multiple linear regression equation. Through comparing the practical test PWV values with the estimate values from regression model, the result showed that there was no significant difference between the model assessment and practical test values (t=0.833, p=.423>.05). Therefore, the regression model is fit for assessing PWV value by height, age, systolic and diastolic pressure.

Through the establishment of evaluation model based on principal component analysis, select 8 principal components from nearly 30 indexes of wine grape. Then we establish the multiple linear regression model and analyse the association between physicochemical indexes of wine grape and wine, and the influence of physicochemical indexes of wine grape and wine on wine quality. Finally study whether we could use the physicochemical indexes to evaluate the wine quality.

Objective method alone is insufficient in measuring discomfort of car seats. It is indirect and does not truly convey the perception and feeling of the sitter. A combination of both objective and subjective method gives better evaluation on discomfort. Seat pressure distribution method was adopted to investigate the static characteristic of a seat. The method was found to be statistically repeatable in measuring sitting of fourteen male subjects in static condition. Subjective discomfort through subjective assessment using a valid and reliable self-established questionnaire together with a body pressure map (BPM) showed increasing discomfort as sitting time increase; which is expected. The short term seat pressure distribution was used to be correlated with subjective assessment. Significant and moderate correlation was observed between four local body parts namely the seat pan bolster, thighs, upper back and lower back with overall seat average pressure BPM used in the subjective evaluation. Multiple linear regression model were established; overall discomfort from averaged pressure from BPM can be predicted from right & left buttock, right & left thigh and upper back & lower back. It was found that R-Sq=93.5%, R-Sq (adj) = 83.7% with moderately adequate predictive ability with predicted R-Sq= 46.77%.

Seasonal variations of trihalomethanes (THMs) and haloacetic acids (HAAs) were investigated within distribution systems of the Yangtze river treatment plant in Nanjing City (China).The investigation was based on one year sampling program, undertaken from the fall and winter of the year 2007 to the spring and summer of the year 2008. A multiple linear regression model was developed to predict THMs and HAAs concentrations in distribution water. Routinely measured parameters including free residual chlorine, ultraviolet light absorbance at 254 nm (UV254), temperature, pH and NH3-N in distribution water was used to develop the model for the prediction of THMs and HAAs. The developed models provided satisfactory estimations of the concentrations of THMs and HAAs and the model regression coefficients of THMs and HAAs are 0.90 and 0.87, respectively. Further, the Durbin-Watson values confirm the reliability of the two models. The results indicate that variations of free residual chlorine, ultraviolet light absorbance at 254 nm (UV254), temperature, pH and NH3-N can described the formation of THMs and HAAs in distribution water by the multiple linear regression technique.

This paper selects energy consumption and annual GDP data of Beijing from the year of 1990 to 2009 as a sample, and adopted the research method of combining the quality and quantity, theory and empirical research, and we also employed the multiple linear regression model to analyze the effect of energy consumption to economic growth and the sensitivity of each effect factor. We wish this paper could provide a support to the future economic growth and policy optimization of energy and industry development of Beijing from theory to data.

Using the Landsat 5 TM images in 2002 as source data，the paper constructed individual tree biomass models of seven principal species based on the data from field surveying and fixed Plots in Tahe and Amur forest Region in Daxiangan Mountains. The remote sensing biomass model between TM images and data from forest fixed Plots was developed by the methods of multiple linear regression and BP neutral net. The result showed that R in multiple linear regression model was 0.764 and the model passed the F test, D-W test and multi-collinearity test. In the independent sample estimation，The neutral net model with the precision of 91.25% was significantly higher than multiple linear regression model with the precision of 81.02%. Although the“black-box”neutral net model could not give the concrete analytical equation, this kind of model with high precision might be applied to estimate the forest biomass in large level forest biomass.

The measurement for riser’s solids concentration is important but difficult. So, a high-efficiency and low-cost new predicted method based on the least square SVM method is proposed. The superficial operated gas velocity Ug and solids circulation rate εs are chosen as the effect factors of the solids concentration. Furthermore, the multiple linear regression model (Linear) and artificial neural net model (ANN) are also used to compare with the SVM model. By analyzing the training time and error, it is proved the SVM model has higher prediction accuracy and forecasting efficiency, which is a better choice for the riser’s solids concentration prediction.

Based on the fairness and benefits of the opportunity to accept higher education, tuition should be paid. The average cost of higher education and the ability to pay tuition which is determined by the average income are two fundamental basics for making the standard of tuition. In order to research the standard of tuition, the paper has focused on two issues: What is the acceptable range of tuition for higher education in China? How much is the reasonable tuition for higher education in China? Then we have established a multiple linear regression model on the basis of the reasonable assumption. Using the Eviews Software, we got that the range of average tuition was [4674.4, 7516.1]. Then we made a sensitivity analysis on the state funding and got the conclusion, tuition of colleges and universities all over our country were reasonable, and that the average tuition was negatively correlated to the state funding to some extent. Through the conclusion, we obtained that the state funding accounted for 25% in training costs of students. When the state funding rose by 250 yuan, the average tuition would decrease by 238 yuan.