In order to clarify the quantitative relationship between construction land changes and carbon emissions, a prediction method for carbon emissions from construction land in central Yunnan urban agglomeration area base...
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In order to clarify the quantitative relationship between construction land changes and carbon emissions, a prediction method for carbon emissions from construction land in central Yunnan urban agglomeration area based on multiple linear regression model was proposed. Taking the central Yunnan urban agglomeration area as the study area, based on the data of construction land from 2011 to 2020, the carbon emission of construction land was predicted by using the multiple linear regression model. There is a positive correlation between the carbon emissions of the central Yunnan urban agglomeration area and the level of construction land use. From 2011 to 2020, average annual growth rate of construction land area was 8.56%, and the average annual growth rate of carbon emissions was 5.75%. The annual growth rate of carbon emissions from 2021 to 2030 is 0.97%, indicating that the government's carbon emission control measures have achieved good results.
this study aims to explore sailboat price prediction methods through the utilization of a multiple linear regression model and the XGBoost algorithm, addressing the pricing challenges in the second-hand sailboat marke...
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Confronted with the unprecedented COVID-19 pandemic, millions of learners have received, are receiving, or will receive multimodal language learning education. This study aims to explore the relationships between vari...
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Confronted with the unprecedented COVID-19 pandemic, millions of learners have received, are receiving, or will receive multimodal language learning education. This study aims to explore the relationships between various factors influencing learners' continuance intention by proposing an innovative multiple linear regression model in multimodal language learning education. Participants were randomly recruited (N = 334) in China who had received multimodal language learning education by combining Massive Open Online Courses, Rain Classroom, and WeChat. The research instrument, a comprehensive questionnaire, was sent through the online system named Questionnaire Star developed by technical experts. A multiplelinearregression analysis was adopted to test the proposed hypotheses and fit the research model. This study confirms the relationships between the Technology Acceptance model-inclusive constructs such as perceived ease of use, perceived usefulness, attitudes toward multimodal language learning education, and continuance intention of participating in multimodal language learning education. The Technology Acceptance model is also associated with other constructs, e.g. Task-technology fit, Individual-technology fit, Openness, and Reputation of multimodal language learning educational institutes, and personal investment in multimodal language learning education. However, personal investment neither directly nor indirectly predicts continuance intention. Educators and designers could make every effort to improve multimodal language learning education to enhance personal investment and foster its association with continuance intention of learners.
作者:
Hai, ChenJinan Univ
Gen Logist Management Off Restorat Project Management Sect Guangzhou 510000 Peoples R China
In order to improve the accuracy of construction project cost budget, based on the previous research, this paper introduces the multiplelinear analysis method, constructs a regressionmodel, and uses the model to bud...
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ISBN:
(纸本)9781665427241
In order to improve the accuracy of construction project cost budget, based on the previous research, this paper introduces the multiplelinear analysis method, constructs a regressionmodel, and uses the model to budget the project cost. The model contains 16 factors. SPSS software is used for weight statistical analysis to extract 4 common factors to improve the structure of the regressionmodel. The reliability of the model is tested by application analysis. The quoted results show that the maximum budget deviation rate is 4.80%, which is within 10%. Therefore, the model can be used as an effective tool for project cost analysis and popularized in the construction field.
Analyze the influencing factors of second-hand housing and build the relevant model using the data on second-hand housing prices in *** R-code analysis is used to construct a prediction model of house prices,and the m...
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Analyze the influencing factors of second-hand housing and build the relevant model using the data on second-hand housing prices in *** R-code analysis is used to construct a prediction model of house prices,and the main factors affecting their changes are *** to the significance test,the model meets the expectation and is ***,it is concluded that the most noticeable impact on housing prices is room distribution and ladder ratio,and the least obvious is trade time.
Climate polarization due to global warming has increased the intensity of drought in some regions, and the need for drought estimation studies to help minimize damage is increasing. In this study, we constructed remot...
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Climate polarization due to global warming has increased the intensity of drought in some regions, and the need for drought estimation studies to help minimize damage is increasing. In this study, we constructed remote sensing and climate data for Boryeong, Chungcheongnam-do, Korea, and developed a model for drought index estimation by classifying data characteristics and applying multiplelinearregression analysis. The drought indices estimated in this study include four types of standardized precipitation indices (SPI1, SPI3, SPI6, and SPI9) used as meteorological drought indices and calculated through cumulative precipitation. We then applied statistical analysis to the developed model and assessed its ability as a drought index estimation tool using remote sensing data. Our results showed that its adj.R-2 value, achieved using cumulative precipitation for one month, was very low (approximately 0.003), while for the SPI3, SPI6, and SPI9 models, the adj.R-2 values were significantly higher than the other models at 0.67, 0.64, and 0.56, respectively, when the same data were used.
Mathematical modeling of economic indices is a challenging topic in crop production *** present study aimed to model the economic indices of mechanized and semimechanized rainfed wheat production systems using various...
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Mathematical modeling of economic indices is a challenging topic in crop production *** present study aimed to model the economic indices of mechanized and semimechanized rainfed wheat production systems using various multiplelinearregression *** study area was Behshahr County located in the east of Mazandaran Province,Northern *** statistical population included all wheat producers in Behshahr County in 2016/17 crop *** input variables were human labor,machinery,diesel fuel,chemical(chemical fertilizers and chemical pesticides)costs,and the income was considered to be the *** results showed that the cost of wheat production in the semimechanized system was higher than that of the mechanized *** both systems,the highest cost was related to agricultural machinery ***,seed cost was lower in the mechanized system than that of the semi-mechanized *** net return indicator was 993.68$ha1 and 626.71$ha1 for the mechanized and semi-mechanized systems,*** average benefit to cost ratio was 3.46 and 2.40 for the mechanized and semi-mechanized systems,respectively,demonstrating the greater profitability of the mechanized *** results of the evaluation of five types of regressionmodels including the Cobb-Douglas,linear,2FI,quadratic and pure-quadratic for the mechanized and semi-mechanized production systems indicated that in the developed Cobb-Douglas model,the R2-value was higher than that of the quadratic model while RMSE and MAPE of the quadratic model were determined to be smaller than that of the Cobb-Douglas ***,the best model to investigate the relationship between input costs and the income of wheat production in both mechanized and semi-mechanized systems was the quadratic model.
The multiple linear regression model is one of the most common models. When the model is applied to economic structure analysis, economic forecasting, policy evaluation and testing, etc., in order to play its role mor...
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The multiple linear regression model is one of the most common models. When the model is applied to economic structure analysis, economic forecasting, policy evaluation and testing, etc., in order to play its role more accurately, it must be ensured that the model does not have heteroscedasticity. Therefore, it is also an important issue to test whether the model has heteroscedasticity. This article mainly sorts out the test methods of multiplelinearregression heteroscedasticity and its applicability, in the hope that the multiplelinearregression heteroscedasticity test can be selected appropriately.
The acceleration of urbanization leads to higher standards and requirements for Internet of Things matching technology. Based on this, the matching technology of Internet of things based on multiplelinearregression ...
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ISBN:
(纸本)9783030152352;9783030152345
The acceleration of urbanization leads to higher standards and requirements for Internet of Things matching technology. Based on this, the matching technology of Internet of things based on multiple linear regression model in urban management is put forward. Data in the Internet of Things are processed accurately. Wireless sensors with optimal functions are selected, and mathematical models are established and solved. Through experimental demonstration, it is concluded that the Internet of Things matching technology based on multiple linear regression model greatly reduces the cost of urban management.
With the continuous development of the social economy, the pollution of the natural environment has become increasingly serious. The purpose of this study was to explore the impact of environmental information disclos...
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