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    Wyświetlanie 1-5 z 5
    Tytuł:
    Predictive Modelling for Characterisation of Organics in Pit Latrine Sludge from Unplanned Settlements in Cities of Malawi
    Autorzy:
    Kalulu, K.
    Thole, B.
    Mkandawire, T.
    Kululanga, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/124540.pdf
    Data publikacji:
    2018
    Wydawca:
    Polskie Towarzystwo Inżynierii Ekologicznej
    Tematy:
    Akaike Information Criterion
    biochemical oxygen demand
    chemical oxygen demand
    faecal sludge characteristics
    multiple linear regression model
    Opis:
    The limited availability of data on faecal sludge characteristics remains one of the major challenges faced by developing countries in proper management of faecal sludge. In view of the limited financial resources and expertise in these developing countries, there is a need to come up with less-resource-intensive approaches for faecal sludge characterisation. Despite being used substantially in wastewater, there is limited evidence on the use of predictive modelling as a tool for cost-effective characterisation of faecal sludge. In this study, first order multiple linear regression modelling is investigated as a less-resource-intensive approach for accurate prediction of organics (biochemical oxygen demand and chemical oxygen demand) in pit latrine sludge. The predictor variables explored in the modelling include pH, electrical conductivity, total solids, total volatile solids, fixed solids and moisture content. The modelling uses data collected from 80 latrines in unplanned settlements of four cities in Malawi. The study shows that it is possible to reliably predict chemical oxygen demand and biochemical oxygen demand in pit latrine sludge using electrical conductivity and total solids, which require low levels of resources and expertise to determine.
    Źródło:
    Journal of Ecological Engineering; 2018, 19, 3; 141-145
    2299-8993
    Pojawia się w:
    Journal of Ecological Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Statistical yielding models of some irrigated vegetable crops in dependence on water use and heat supply
    Autorzy:
    Vozhehova, Raisa
    Kokovikhin, Sergii
    Lykhovyd, Pavlo V.
    Balashova, Halyna
    Lavrynenko, Yuriy
    Biliaieva, Iryna
    Markovska, Olena
    Powiązania:
    https://bibliotekanauki.pl/articles/292829.pdf
    Data publikacji:
    2020
    Wydawca:
    Instytut Technologiczno-Przyrodniczy
    Tematy:
    linear model
    multiple linear regression analysis
    onion
    potato
    tomato
    yield modelling
    Opis:
    Statistical analysis is helpful for better understanding of the processes which take place in agricultural ecosystems. Particular attention should be paid to the processes of crops’ productivity formation under the influence of natural and anthropogenic factors. The goal of our study was to provide new theoretical knowledge about the dependence of vegetable crops’ productivity on water supply and heat income. The study was conducted in the irrigated conditions of the semi-arid cold Steppe zone on the fields of the Institute of Irrigated Agriculture of NAAS, Kherson, Ukraine. We studied the historical data of productivity of three most common in the region vegetable crops: potato, tomato, onion. The crops were cultivated by using the generally accepted in the region agrotechnology. Historical yielding and meteorological data of the period 1990–2016 were used to develop the models of the vegetable crops’ productivity. We used two approaches: development of pair linear models in three categories (“yield – water use”, “yield – sum of the effective air temperatures above 10°C”); development of complex linear regression models taking into account such factors as total water use, and temperature regime during the crops’ vegetation. Pair linear models of the crops’ productivity showed that the highest effect on the yields of potato and onion has the water use index (R2 of 0.9350 and 0.9689, respectively), and on the yield of tomato – temperature regime (R2 of 0.9573). The results of pair analysis were proved by the multiple regression analysis that revealed the same tendencies in the crop yield formation depending on the studied factors.
    Źródło:
    Journal of Water and Land Development; 2020, 45; 190-197
    1429-7426
    2083-4535
    Pojawia się w:
    Journal of Water and Land Development
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Determination of soil infiltration rate equation based on soil properties using multiple linear regression
    Autorzy:
    Harisuseno, Donny
    Cahya, Evi N.
    Powiązania:
    https://bibliotekanauki.pl/articles/1844413.pdf
    Data publikacji:
    2020
    Wydawca:
    Instytut Technologiczno-Przyrodniczy
    Tematy:
    infiltration rate
    model performance
    multiple linear regression
    soil property
    Opis:
    Infiltration process plays important role in water balance concept particularly in runoff analysis, groundwater recharged, and water conservation. Hence, increasing knowledge concerning infiltration process becomes essential for water manager to gain an effective solution to water resources problems. This study employed multiple linear regression for estimating infiltration rate where the soil properties used as the predictor variable and measured infiltration rate as the response variable. Field measurement was conducted at sixteen points to obtain infiltration rate using double ring infiltrometer and soil properties namely soil porosity, silt, clay, sand content, degree of saturation, and water content. The result showed that measured infiltration rate had an average initial infiltration rate (f0) of 6.92 mm∙min–1 and final infiltration rate (fc) of 1.49 mm∙min–1. Soil porosity and sand content showed a positive correlation with infiltration rate by 0.842, 0.639, respectively, while silt, clay, water content, and degree of saturation exhibited a negative correlation by –0.631, –0.743, –0.66 and –0.49, respectively. Three types of regression equations were established based on type of soil properties used as predictor variables. The model performance analysis was conducted for each equation and the result shows that the equation with five predictor variables fMLR_3 = – 62.014 + 1.142 soil porosity – 0.205 clay, – 0.063 sand – 0.301, silt + 0.07 soil water content with R2 (0.87) and Nash–Sutcliffe (0.998) gave the best result for estimating infiltration rate. The study found that soil porosity contributes mostly to the regression equation that indicates great influence in controlling soil infiltration behavior.
    Źródło:
    Journal of Water and Land Development; 2020, 47; 77-88
    1429-7426
    2083-4535
    Pojawia się w:
    Journal of Water and Land Development
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Modele ekonometryczne jako narzędzie sterowania procesami technologicznymi
    Econometric models as a tool for technological process control
    Autorzy:
    Wołkowicz, Artur
    Powiązania:
    https://bibliotekanauki.pl/articles/424875.pdf
    Data publikacji:
    2015
    Wydawca:
    Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
    Tematy:
    exponential smoothing model with creeping trend
    Brown model
    regression function
    multiple and threshold regression
    linear programming
    Opis:
    This paper presents a proposal for process control applications based on econo-metric models. They are a tool which aim is to determine short-term forecasts, which are the basis to control the devices of production infrastructure. The article describes the application of the method of forecast errors corrective device in a real production process. Econometric models are presented: the exponential smoothing model and creeping trend adaptive model with harmonic scales. The calculations are used and the regression function is indicated by the linear programming problem. The method is presented on the example of classical tech-nological process used in the energy sector. The study indicates the possibility of another perspective on the control processes, not necessarily based on the existing methods of regu-lation. The idea of this study is to demonstrate the possibility of using econometrics in the industry.
    Źródło:
    Econometrics. Ekonometria. Advances in Applied Data Analytics; 2015, 2 (48); 67-77
    1507-3866
    Pojawia się w:
    Econometrics. Ekonometria. Advances in Applied Data Analytics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    IS MULTIPLE LINEAR REGRESSION THE PROPER TOOL OF MODELLING A BEHAVIOUR OF REAL SYSTEMS?
    Autorzy:
    Nowak, Jacek
    Powiązania:
    https://bibliotekanauki.pl/articles/453283.pdf
    Data publikacji:
    2009
    Wydawca:
    Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
    Tematy:
    model of real system
    multiple linear regression
    real system structure
    discrete automaton
    „black box” modelling
    quality of approximation
    Opis:
    Methodological assumption that multiple linear regression is an adequate tool of modelling the behaviour of real systems is checked. To do this the experiment is organised on the basis of simple “real” system represented as finite discrete automaton. Main result is that in situation of “black box” modelling the approximation of output variables with multiple linear regressions (from several samples and under different conditions) may not fulfil any of criterions of feasible approximation of systems behaviour, also in situations where real relation between input and output variables is strictly linear and only one of variables is omitted.
    Źródło:
    Metody Ilościowe w Badaniach Ekonomicznych; 2009, 10, 1; 194-206
    2082-792X
    Pojawia się w:
    Metody Ilościowe w Badaniach Ekonomicznych
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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