multiple linear regression
در نشریات گروه محیط زیست-
شهرنشینی به دلیل تخریب کیفیت زیستگاه و تکه تکه شدن آن به عنوان مهم ترین محرک انقراض گونه های مختلف گیاهی و جانوری در قرن حاضر به شمار می آید. از این رو، بررسی تغییرات موزایک موزاییک کاربری و پوشش اراضی می تواند اطلاعات مفیدی در مورد تغییر فرآیندهای اکولوژیکی بخصوص تغییر در تنوع پرندگان در سیماهای شهری فراهم کند. عملیات مشاهده و ثبت پرندگان از فروردین تا اردیبهشت سال 1400 بین ساعات 8 تا 11 صبح با سه تکرار در 55 نقطه مستقر بر 11 ترانسکت (5 نقطه در هر ترانسکت) صورت گرفت. ترانسکت ها و نقاط با بررسی شیب تغییرات کاربری و پوشش اراضی در شیب روستا-شهر انتخاب شدند. سپس تعداد 10 متغیر مربوط به وسعت، متوسط فاصله و تراکم پوشش سبز، شبکه جاده و سکونتگاه در 4 بافر دایره ای با شعاع های 750، 1500، 2250 و 3000 در هر نقطه مشاهده پرنده کمی گردید و ارتباط آن با شاخص تنوع شانون پرندگان مشاهده شده با استفاده از مدل رگرسیون خطی چندگانه بررسی شد. در مشاهدات، تعداد 2085 قطعه فرد پرنده متعلق به 46 گونه پرنده مشاهده گردید. گنجشک خانگی نیز با تعداد 1381 قطعه فرد به عنوان فراوانترین گونه پرنده مشاهده شده و ثبت گردید. از بین پارامترهای مورد استفاده، درصد پوشش سبز در بافر 1500 متر، درصد پوشش جاده در بافر 750 متر، وسعت نزدیک ترین پوشش سبز، فاصله تا نزدیکترین پوشش سبز و متوسط فاصله تا نزدیک ترین پوشش سبز در بافر 2250 متر به عنوان متغیرهای پیش بینی کننده تنوع شانون در مدل رگرسیون تعیین شدند (0/64 =r2). یافته های این تحقیق نشان داد که وسعت کم لکه های سبز، فاصله زیاد آن ها نسبت به یکدیگر و تراکم بالای شبکه جاده ای، از مهم ترین عوامل کاهش حضور و تنوع گونه های پرندگان در محیط های شهری است. اگرچه مناطق نزدیک به مرز فیزیکی شهری، تنوع پرندگان بالاتری را نشان داد، اما کاهش شدید آن ها به سمت هسته ی مرکزی شهر را می توان با جانمایی دقیق پارک های سبز شهری و کاهش اثر ترافیک در مناطق نزدیک به آن تعدیل کرد.
کلید واژگان: رگرسیون خطی چندگانه، شاخص تنوع شانون، پوشش سبز، شبکه جاده، کاربری اراضیUrbanization is considered the most important extinction driver of various fauna and flora species in the present century due to the degradation of habitat quality and its fragmentation. Therefore, investigation of changes in the land use land cover mosaic can provide useful information about the alteration of ecological processes, especially changes in bird diversity in urban landscapes. Bird survey was carried out from April to May 1400 between 8 and 11 am with three repetitions at 55 points located on 11 transects (5 points per transect). Transects and points were selected by examining land use and land cover changes on the rural-urban gradient. Then, 10 variables related to the area, mean distance and density of green cover, road network and habitat were computed in 4 circular buffers with radii of 750, 1500, 2250 and 3000 at each point of bird observation to assess their relationship with the Shannon diversity index using the multiple linear regression model. 2085 birds belonging to 46 bird species were observed. The domestic sparrow was found as the most abundant bird species with 1381 individuals. Among the independent parameters, percentage of green cover in buffer 1500 m, percentage of road cover in buffer 750 m, area of the nearest green cover, distance to the nearest green cover and mean distance to the nearest green cover in buffer 2250 m as variables were entered in the regression model (r2 = 0.64) as predictors of diversity Shannon. The findings of this study showed that the area of small green spaces, their long distance from each other and the high density of the road network are the most important factors in reducing the presence and diversity of bird species in the urban environment. Although areas close to the urban physical border showed higher bird diversity, their sharp decline toward the city center could be offset by accurate locating of urban green parks and reduction of traffic effects in nearby areas.
Keywords: Multiple linear regression, Shannon Diversity Index, Green Coverage, Road Network, landuse -
Particulate matter, as one of the biggest problems of air pollution in metropolises, is the cause of many respiratory, lung and cardiovascular diseases, which timely awareness and announcement can reduce these adverse effects on human health. Therefore, considering that children are more exposed and more sensitive to this pollution, this research was conducted to introduce an evaluated mathematical model to predict PM2.5 concentration levels, indoor selected preschools located in one of centeral district of Tehran (district 6), using determination of related factors to PM2.5 concentration. Classroom environmental information, Meteorological information and urban fixed monitoring stations data were collected through measuring Indoor and outdoor classroom PM2.5 concentrations using direct-reading instruments, adjusted questionnaire and conducted organizations, simultaneously. Results showed the spring and autumn had the lowest and highest indoor and outdoor concentrations (17.1 and 20.5 μg m-3 & 48.7 and 78 μg m-3respectively). Multiple linear regression model was introduced by statistical analysis and the results of indoor PM2.5 concentration predictions were compared and evaluated with measured data. The results of introduced this model, consisting of identifying seven main factors affecting the mean concentrations of indoor PM2.5, including outdoor PM2.5, the number of pupils, ambient temperature, wind speed, wind direction and open area of the doors and windows, showed that it has good accuracy (R2 = 0.705) and significantly correlated(p < 0.001). The Multiple Linear Regression Model can be used with good accuracy to predict indoor PM2.5 concentration of preschool classes in Tehran.
Keywords: multiple linear regression, PM2.5, preschool, Tehran air quality -
The objective of this study was to develop a forecast model to determine the rate of generation of municipal solid waste in the municipalities of the Cuenca del Cañón del Sumidero, Chiapas, Mexico. Multiple linear regression was used with social and demographic explanatory variables. The compiled database consisted of 9 variables with 118 specific data per variable, which were analyzed using a multicollinearity test to select the most important ones. Initially, different regression models were generated, but only 2 of them were considered useful, because they used few predictors that were statistically significant. The most important variables to predict the rate of waste generation in the study area were the population of each municipality, the migration and the population density. Although other variables, such as daily per capita income and average schooling are very important, they do not seem to have an effect on the response variable in this study. The model with the highest parsimony resulted in an adjusted coefficient of 0.975, an average absolute percentage error of 7.70, an average absolute deviation of 0.16 and an average root square error of 0.19, showing a high influence on the phenomenon studied and a good predictive capacity.
Keywords: Explanatory variables, forecast model, Multiple Linear Regression, statistical analysis, Waste generation -
Solvatochromic properties of a series of bis(3–substituted derivatives of acetylacetone copper(II) (X-acacH, X = Cl, H. CH) complexes were studied. All the complexes demonstrated negative 3 solvatochromism. Among the complexes the Cu(Cl-acac), demonstrated the most solvatochromism. A multi-parametric equation 2 has been utilized to explain the solvent effect on the d-d transition of the complexes using SPSS/PC software. The stepwise multiple linear regression (SMLR) method demonstrated that the donor power of the solvent plays the most important role in the solvatochromism of the compounds.Keywords: Solvatochromism, Multiple linear regression, Visible spectroscopy, Copper (II) complex, Acetylacetonate
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