Engineering topics

Badiru, Adedeji B

Publications and source records attributed to Badiru, Adedeji B.

3 records

DOE OSTI2012

An Economic Evaluation Framework for Assessing Renewable Energy Projects

It is becoming increasingly imperative to integrate renewable energy, such as solar and wind, into electricity generation due to increased regulations on air and water pollution and a sociopolitical desire to develop more clean energy sources. This increased spotlight on renewable energy requires evaluating competing projects using either conventional economic analysis techniques or other economics-based models and approaches in order to select a subset of the projects to be funded. Even then, there are reasons to suspect that techniques applied to renewable energy projects may result in decisions that will reject viable projects due to the use of a limited number of quantifiable and tangible attributes about the projects. This paper presents a framework for economic evaluation of renewable energy projects. The framework is based on a systems approach in which the processes within the entire network of the system, from generation to consumption, are accounted for. Furthermore, the framework uses the concept of fuzzy system to calculate the value of information under conditions of uncertainty.

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DOE OSTI2011

Online Support Vector Regression with Varying Parameters for Time-Dependent Data

Support vector regression (SVR) is a machine learning technique that continues to receive interest in several domains including manufacturing, engineering, and medicine. In order to extend its application to problems in which datasets arrive constantly and in which batch processing of the datasets is infeasible or expensive, an accurate online support vector regression (AOSVR) technique was proposed. The AOSVR technique efficiently updates a trained SVR function whenever a sample is added to or removed from the training set without retraining the entire training data. However, the AOSVR technique assumes that the new samples and the training samples are of the same characteristics; hence, the same value of SVR parameters is used for training and prediction. This assumption is not applicable to data samples that are inherently noisy and non-stationary such as sensor data. As a result, we propose Accurate On-line Support Vector Regression with Varying Parameters (AOSVR-VP) that uses varying SVR parameters rather than fixed SVR parameters, and hence accounts for the variability that may exist in the samples. To accomplish this objective, we also propose a generalized weight function to automatically update the weights of SVR parameters in on-line monitoring applications. The proposed function allows for lower and upper bounds for SVR parameters. We tested our proposed approach and compared results with the conventional AOSVR approach using two benchmark time series data and sensor data from nuclear power plant. The results show that using varying SVR parameters is more applicable to time dependent data.

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DOE OSTI2011

Handbook of Industrial Engineering Equations, Formulas, and Calculations

The first handbook to focus exclusively on industrial engineering calculations with a correlation to applications, Handbook of Industrial Engineering Equations, Formulas, and Calculations contains a general collection of the mathematical equations often used in the practice of industrial engineering. Many books cover individual areas of engineering and some cover all areas, but none covers industrial engineering specifically, nor do they highlight topics such as project management, materials, and systems engineering from an integrated viewpoint. Written by acclaimed researchers and authors, this concise reference marries theory and practice, making it a versatile and flexible resource. Succinctly formatted for functionality, the book presents: Basic Math Calculations; Engineering Math Calculations; Production Engineering Calculations; Engineering Economics Calculations; Ergonomics Calculations; Facility Layout Calculations; Production Sequencing and Scheduling Calculations; Systems Engineering Calculations; Data Engineering Calculations; Project Engineering Calculations; and Simulation and Statistical Equations. It has been said that engineers make things while industrial engineers make things better. To make something better requires an understanding of its basic characteristics and the underlying equations and calculations that facilitate that understanding. To do this, however, you do not have to be computational experts; you just have to know where to get the computational resources that are needed. This book elucidates the underlying equations that facilitate the understanding required to improve design processes, continuously improving the answer to the age-old question: What is the best way to do a job?

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