assessment of the expected construction company’s net profit using neural network and multiple regression models

Clicks: 366
ID: 133608
2013
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #4 of 60 articles by views in der pharmacia lettre

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Net profit is an important financial performance indicator for any construction firm. Firm financial managers should strive to maximize this net profit. Modeling company’s net profit helps to investigate the serious effects of the different financial conditions on the expected net profit for the construction companies working in the Egyptian market. It simply helps financial managers to make sure that their companies business operations are running in a profitable manner. This research aims to develop a mathematical model for assessing the expected net profit of any construction company. To achieve the research objective, four steps were performed. First, the main factors affecting firms’ net profit were identified. Second, pertinent data regarding the net profit factors were collected. Third, two different net profit models were developed using the Multiple Regression (MR) and the Neural Network (NN) techniques. The validity of the proposed models was also investigated. Finally, the results of both MR and NN models were compared to investigate the predictive capabilities of the two models.
Reference Key
mohamad2013ainassessment Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;H.H. Mohamad;A.H. Ibrahim;H.H. Massoud
Journal der pharmacia lettre
Year 2013
DOI
10.1016/j.asej.2012.11.008
URL
http://www.sciencedirect.com/science/article/pii/S2090447912001165
Keywords
Neural network civil engineering (general)

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.