A generalization of the orthogonal regression technique for life cycle inventory

Maurizio Cellura, Antonino Marvuglia, Marcello Pucci

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Abstract

Life cycle assessment (LCA) is a method used to quantify the environmental impacts of a product, process, or service across its whole life cycle. One of the problems occurring when the system at hand involves processes delivering more than one valuable output is the apportionment of resource consumption and environmental burdens in the correct proportion amongst the products. The mathematical formulation of the problem is represented by the solution of an over-determined system of linear equations. The paper describes the application of an iterative algorithm for the implementation of least square regression to solve this over-determined system directly in its rectangular form. The applied algorithm dynamically passes from an Ordinary Least Squares (OLS) problem to the regression problems known as Total Least Squares (TLS) and Data Least Squares (DLS). The obtained results suggest further investigations. In particular, the so called constrained least squares method is identifed as an interesting development of the methodology.
Lingua originaleEnglish
pagine (da-a)51-71
Numero di pagine21
RivistaInternational Journal of Agricultural and Environmental Information Systems
Volume3
Stato di pubblicazionePublished - 2012

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Life cycle
Linear equations
Environmental impact

All Science Journal Classification (ASJC) codes

  • Information Systems

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title = "A generalization of the orthogonal regression technique for life cycle inventory",
abstract = "Life cycle assessment (LCA) is a method used to quantify the environmental impacts of a product, process, or service across its whole life cycle. One of the problems occurring when the system at hand involves processes delivering more than one valuable output is the apportionment of resource consumption and environmental burdens in the correct proportion amongst the products. The mathematical formulation of the problem is represented by the solution of an over-determined system of linear equations. The paper describes the application of an iterative algorithm for the implementation of least square regression to solve this over-determined system directly in its rectangular form. The applied algorithm dynamically passes from an Ordinary Least Squares (OLS) problem to the regression problems known as Total Least Squares (TLS) and Data Least Squares (DLS). The obtained results suggest further investigations. In particular, the so called constrained least squares method is identifed as an interesting development of the methodology.",
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T1 - A generalization of the orthogonal regression technique for life cycle inventory

AU - Cellura, Maurizio

AU - Marvuglia, Antonino

AU - Pucci, Marcello

PY - 2012

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N2 - Life cycle assessment (LCA) is a method used to quantify the environmental impacts of a product, process, or service across its whole life cycle. One of the problems occurring when the system at hand involves processes delivering more than one valuable output is the apportionment of resource consumption and environmental burdens in the correct proportion amongst the products. The mathematical formulation of the problem is represented by the solution of an over-determined system of linear equations. The paper describes the application of an iterative algorithm for the implementation of least square regression to solve this over-determined system directly in its rectangular form. The applied algorithm dynamically passes from an Ordinary Least Squares (OLS) problem to the regression problems known as Total Least Squares (TLS) and Data Least Squares (DLS). The obtained results suggest further investigations. In particular, the so called constrained least squares method is identifed as an interesting development of the methodology.

AB - Life cycle assessment (LCA) is a method used to quantify the environmental impacts of a product, process, or service across its whole life cycle. One of the problems occurring when the system at hand involves processes delivering more than one valuable output is the apportionment of resource consumption and environmental burdens in the correct proportion amongst the products. The mathematical formulation of the problem is represented by the solution of an over-determined system of linear equations. The paper describes the application of an iterative algorithm for the implementation of least square regression to solve this over-determined system directly in its rectangular form. The applied algorithm dynamically passes from an Ordinary Least Squares (OLS) problem to the regression problems known as Total Least Squares (TLS) and Data Least Squares (DLS). The obtained results suggest further investigations. In particular, the so called constrained least squares method is identifed as an interesting development of the methodology.

UR - http://hdl.handle.net/10447/62106

M3 - Article

VL - 3

SP - 51

EP - 71

JO - International Journal of Agricultural and Environmental Information Systems

JF - International Journal of Agricultural and Environmental Information Systems

SN - 1947-3192

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