نتایج جستجو برای: multiple linear regression mlr
تعداد نتایج: 1407189 فیلتر نتایج به سال:
The apoptosis-inducing activity data of a series of 4-aryl-4H-chromenes based on three cell lines (human breast cancer cell line T47D, human non-smal cell lung cancer cell line H1299, and human colorectal cancer cell line DLD-1) have been subjected to quantitative structure-activity relationship (QSAR) analysis. A collection of chemometrics methods including multiple linear regression (MLR), fa...
background: municipal solid waste (msw) is the natural result of human activities. msw generation modeling is of prime importance in designing and programming municipal solid waste management system. this study tests the short-term prediction of waste generation by artificial neural network (ann) and principal component-regression analysis. methods: two forecasting techniques are presented in...
The quantitative structure property relationship (QSPR) for supercooled liquid vapour pressures (pL) of polybrominated diphenyl ethers (PBDEs) was investigated. The molecular distance–edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and log pL was modelled by multivariate linear regression (MLR) and an artificial neural network...
For forecasting the maximum 5-day accumulated precipitation over the winter season at lead times of 3, 6, 9 and 12 months over Canada from 1950 to 2007, two nonlinear and two linear regression models were used, where the models were support vector regression (SVR) (nonlinear and linear versions), nonlinear Bayesian neural network (BNN) and multiple linear regression (MLR). The 118 stations were...
Energy efficiency in buildings requires having good prediction of the variables that define the power consumption in the building. Temperature is the most relevant of these variables because it affects the operation of the cooling systems in summer and the heating systems in winter, while being also the main variable that defines comfort. This paper presents the application of classical methods...
physiographic characteristics and climatic conditions are factors which contributing to river flow regime and understanding of relations between these factors and river flow in a basin result in its application for the ungauged sub-basins river flow prediction. in this research the relation between physiographic and climatic parameters of golestan province and rivers flow were examined by appli...
Nitrogen is a vital element in crops, and its management is a key measure to improve their yield and quality. Real-time monitoring of crop nitrogen content is needed to optimize products and crop production. In this paper we use chlorophyll fluorescence source to obtain pepper leaf image for machine vision and digital image processing and establish a greenhouse pepper leaf nitrogen content rapi...
Background and Objectives: Considering the importance of safety evaluation of fish and seafood from capture to purchase, rapid and nondestructive methods are in urgent need for seafood industry. This study aimed to assess the application of hyperspectral imaging (HSI: 430-1010 nm) for prediction of total volatile basic nitrogen (TVB-N) in Japanese-threadfin bream (Nemipterusjaponicus) fillets, ...
This chapter deals with computation of viscosity of 35 alcohols at 20C with the computational tools Multi-linear Regression (MLR) and Associative Neural Network(ASNN) . The four descriptors are used which are variable Zagreb index, Number of Hydroxyl Groups(NOH), Molecular Weight (MW) and Number of Carbon atoms (Nc). MLR is used to optimize the parameter(λ) in the variable Zagreb index by minim...
Knowledge of patients affective state could prove to be crucial for health-care professionals in both diagnosis and treatment, however, this requires patients to report how they feel. In practice the sampling rate of affective states needs to be kept low, in order to ensure that the patients can rest. Furthermore using traditional methods of measuring affective states, is not always possible, e...
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