Abstracts - faqs.org

Abstracts

Business, international

Search abstracts:
Abstracts » Business, international

Nonparametric econometric modelling: a neural network approach

Article Abstract:

The feasibility of applying neural networks to nonparametric econometric modelling is considered. The approach is demonstrated using real-life data on the prices and consumption of durables, non-durables and services in the US between 1932 and 1972. Its implementation, however, required the pre-processing of raw data, the imposition of constraints during the training stage, and cross-validation of the generated function.

Author: Wang, Shouhong
Publisher: Elsevier B.V.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1996
Models, Econometrics

User Contributions:

Comment about this article or add new information about this topic:

CAPTCHA


Analyzing mathematical models with inductive learning networks

Article Abstract:

The viability of inductive learning networks to mathematical model analysis was investigated. Specifically, the group method of data handling and feedforward neural networks trained using the backpropagation technique were applied to analyze a facility location model. To this end, the key input and output variables and the relations between unknown model parameters and the corresponding objective functions were derived.

Author: Sharda, Ramesh, Steiger, David M.
Publisher: Elsevier B.V.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1996
Evaluation, Mathematical models, Decision support systems

User Contributions:

Comment about this article or add new information about this topic:

CAPTCHA


Parametric distance functions vs. nonparametric neural networks for estimating road travel distances

Article Abstract:

The viability of nonparametric neural networks for approximating road travel distances was investigated. Specifically, regression neural networks based on Gaussian kernels and backpropagation-trained multilayer perceptrons were compared to parametric distance functions in actual distance estimation studies using Turkish cities. The results showed that the neural networks delivered more accurate measurements.

Author: Alpaydin, Ethem, Altinel, I. Kuban, Aras, Necati
Publisher: Elsevier B.V.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1996
Measurement, Traffic estimation, Distances, Distance measurement

User Contributions:

Comment about this article or add new information about this topic:

CAPTCHA


Subjects list: Operations research, Management science, Usage, Computer networks, Case studies, Neural networks, Research
Similar abstracts:
  • Abstracts: Dynamic grouping of parts in flexible manufacturing systems - a self-organizing neural networks approach. Editorial
  • Abstracts: Hot money, hot problem. A new approach. Jardine Fleming: knuckles rapped
  • Abstracts: She stoops to conquer. Long, winding road: political reform won't happen overnight
  • Abstracts: Gun-shy. Hard times roll: no end in sight for economic, political crises. Vintage dreams; Thai tycoon produces a very drinkable wine
  • Abstracts: Gloom (continued). Building further success. Mid-life crisis; Asian Development Bank gropes ahead
This website is not affiliated with document authors or copyright owners. This page is provided for informational purposes only. Unintentional errors are possible.
Some parts © 2025 Advameg, Inc.